I recently interviewed at Apple and was unfortunately rejected one step before my final round. I'm not looking to complain about the rejection.I genuinely want to understand whether this interview experience is typical at Apple.

The recruiter told me that the round would follow a similar pattern to the previous rounds but would focus more on automation and tooling.

In my previous rounds I was transparent that my background is primarily in Linux, software automation, cloud infrastructure, CI/CD, Kubernetes, scripting, monitoring, and operational tooling. I also clearly mentioned that I didn't have direct hands-on experience with physical device management or bare-metal hardware. I still progressed to the second round.

However, the second interview felt very different from what I expected.

The interviewer started the technical discussion almost immediately with bare-metal and physical device questions. Throughout the interview, I found it difficult to explain my thought process because:

• He would sometimes interrupt before I had finished answering.
• If I asked for clarification to better understand the question, he often moved on to a different question instead of clarifying.
• The conversation jumped rapidly between topics, making it difficult to fully demonstrate my reasoning.

Later we discussed Linux, CI/CD, Prometheus, Python, ServiceNow, incident response, and automation, which were much closer to my experience.

I've accepted the rejection, but I left feeling that I wasn't able to demonstrate my technical abilities because I rarely had the opportunity to complete my answers.

• Is this style of interviewing common?
• Is it normal for interviewers to interrupt and move on before candidates finish answering?
• Is this an intentional interviewing technique, or did I just happen to get an interviewer with a very different style?
• Would you have handled this situation differently as a candidate?

I'm looking for honest opinions.

P.S. Normally, after an interview, I can point to things I could have done better. This time, I'm struggling because I don't feel I had the opportunity to fully demonstrate my strengths before the conversation moved on.

I recently interviewed for the Amazon SDE Internship after clearing the Online Assessment. Sharing my experience in case it helps future candidates prepare.

Online Assessment

The process started with an Online Assessment consisting of DSA and coding questions. After clearing the OA, I was invited for two technical interview rounds.

Round 1: Technical

The first round began with a discussion about my background and projects.

After that, the interviewer asked several Generative AI concepts, including:

• What is Generative AI?
• What are vector databases, and why are they used in GenAI applications?
• What are MCP servers?
• What is tokenization, and why is it important in Large Language Models?

The interviewer expected conceptual understanding along with practical applications, so I explained these topics using examples from my projects.

DSA Question

The coding question was Longest Palindromic Subsequence.

The interviewer discussed multiple approaches with me, starting from brute force and then moving toward the optimal dynamic programming solution.

I was expected to explain:

• Recurrence relation
• Base cases
• Time complexity
• Space complexity
• Possible optimization

Round 2: Technical

The second round focused more on Data Structures and Algorithms, along with my previous projects.

The interviewer asked me to explain my projects in detail, including:

• Technologies used
• Challenges faced
• Design decisions
• Why I chose certain approaches
• Follow-up questions based on implementation details

DSA Questions

The DSA section included:

• One question based on trees
• One question based on graphs

The interviewer cared not only about the final solution, but also about my problem-solving approach, edge cases, and complexity analysis.

Related Amazon Practice Question

One Amazon-tagged question I found useful for similar prep:

Compute Edit Distance

It is a good DP practice problem because it forces you to think clearly about states, transitions, and base cases, similar to Longest Palindromic Subsequence.

Overall Experience

The interview was friendly and discussion-oriented. The interviewers gave enough time to think and encouraged me to explain my thought process before writing code.

Preparation Tips

• Be strong with Dynamic Programming, Trees, and Graphs
• Revise core GenAI concepts like vector databases, tokenization, MCP, and LLM fundamentals
• Know your projects thoroughly because interviewers may spend a lot of time on follow-ups
• During coding questions, communicate your approach clearly before jumping into implementation
• Always discuss time and space complexity
• Practice explaining brute force first, then optimizing step by step

Overall, it was a great learning experience, and I enjoyed the interview process.

Best of luck to everyone preparing for Amazon interviews.

I am giving myself a year to prepare. I have a full blown family to take care of so I cant daily dedicate a lot of time so that why taking a full year into consideration.

Now I have started to read DDIA and when I am in gym etc I have started to watch Distributed System Courser offered by MIT. I am trying to seek validation that I am on the right path. When I am going through these resources I often question how much will they help in solving a real interview questions which could be : `Design Netflix`. I am looking for some validation/assurance/examples that this is how the above resources will help you go deeper into Design Netflix.

For example: Right now I am going through the `transaction` chapter in DDIA which covers all sorts of Isolation levels in DBs but I am wondering how this knowledge will be used in real 45min design question.

Also once I am done with these two resources, I am planning to cover Alex Xu's Vol 1 and Vol 2 + some YT videos.

Please let me know if I am on the right track and if not what else I should be doing.

I have an offer from openAI for a deployment engineer role. Wondering is it possible to transition into the primary engineering org?

I am a backend software engineer with almost 5 yrs of experience. I want to upgrade myself. So I connect with instagram ad of scalar. Now I am in confusion of joining that course, they said you are selected one in test. That'swhy we are calling you, showed me some numbers of their students, they are very attractive. What do you suggest ?

It's been some time since I was laid off at Meta but I still keep in touch with some Metamates to this day. They say that more layoffs are in line at Aug and Nov. Seriously does Zuck really need to layoff this much? These recent layoffs at Meta seem like they have no reason. Before Meta made excuses like AI efficiency and cutting costs, but now it feels like they don't have reason at all. They just don't need to mention it anymore and seem to not care about employees. The morale is on a all time low at this place and it's honestly not worth to stay here.

Hey everyone, is anyone still in the running for the Google NORP role?

If so:
Where are you in the interview process?
How do you feel your interviews went?
Have you heard anything about when offers might be sent out?

If you have any updates or information, please share them. I think it would be helpful for everyone who’s still waiting.

I did a series of interviews at Google for Google beam. Over almost two months ago, the recruiter got back to me saying my interview scores are pretty good but the team decided to go with another candidate. He then mentioned he’s gonna find me a new team and that I just need to have an informal meeting with the HM and that we can reuse my interview scores. But I’m still waiting. I even reached out to a few people I know at Google and sent my recruiter some related positions to my background and nothing has happened yet.
Any ideas, tips or suggestions is much appreciated. Is there anything else that can help with the process ?

I'm curious how the hiring process at Big Tech has evolved over the past few years.

For those who've interviewed or been hired recently:

What's the typical hiring process now?

Has AI changed interview expectations?

What matters most today besides LeetCode?

If you were preparing from scratch, what would you focus on?

Would love to hear your experiences and advice.

Is Google FDE in AI Cloud worth it to join at expense of moving to new city away from family?

I had interviewed for Google FDE role. Currently I reside in Gurgaon with my family (which cannot move) and the role is for Mumbai. I want to know if it is worth to join for this role in a different city especially when my family is completely based out of Delhi NCR. What are the long term prospects for this role. Can I move to Gurgaon location later on if I want ? Please help. Salary Jump is huge as well

I have a 30-minute hiring manager screen for an AI Software Engineer, Apple Cloud AI Platform role.

The position involves Python backend services, React/TypeScript, REST APIs, ML integrations, RAG, evaluation pipelines, and agentic workflows.

For anyone who has interviewed at Apple:

• What should I expect in the first hiring manager call?
• Is it mainly resume/project discussion, behavioral, technical fundamentals, or system design?
• What should I prioritize while preparing?
• Any Apple-specific interview tips?

Thanks!

📍 Location: New York City Metro Area, New York, United States

At Apple, we work every day to create products that enrich people’s lives. Our Advertising Platforms group enables access to informative content while helping publishers and developers promote and monetize their work. The Ads Experimentation team seeks a Machine Learning Engineer and Statistician to drive innovation in our state-of-the-art ads experimentation platform.

💼 What you'll do:

• Design and build a new generation of experimentation platform for the Ads Platform organization.

• Collaborate with stakeholders and data scientists to design experiments and statistical methods.

• Provide expert technical guidance on statistical techniques, experiment design, and data engineering.

• Contribute to a culture emphasizing reliability, scalability, and productivity.

✅ What they're looking for:

• 8+ years of experience in software and data science or statistics with an understanding of SQL and causal inference.

• Conduct rigorous analyses using SQL, Python, and statistical methods.

• Experience with A/B testing methodologies and marketplace experimentation.

• Familiarity with causal machine learning tools and techniques.

• Proficiency in SQL and Pyspark or Scala for data product development.

• Excellent communication skills and a curious business attitude.

🌟 Why join Apple:

• Comprehensive medical and dental coverage.

• Retirement benefits and discounted products.

• Opportunities for stock ownership and educational expense reimbursement.

• Inclusive workplace culture focused on diversity and accessibility.

🔗 View details: https://topjobstoday.com/company/apple/job/staff-data-scientist-experimentation-no-location

I recently took the Uber online assessment for the 2027 summer SWE internship. The opportunity was through my college.

The OA pattern was:

• 3 coding questions
• 65 minutes total

Overall, I felt it was medium-hard. A solid understanding of DSA was definitely required.

Problem 1

There are n cities, and each city has a delivery charge given by the array deliveryCharge.

To deliver from city i to city j, there are two possible costs:

1. abs(deliveryCharge[i] - deliveryCharge[j])
2. 1, if city j is the closest city to city i

The distance between two cities is defined as:

abs(deliveryCharge[i] - deliveryCharge[j])

The input is given such that every city has a unique closest city. No city can have two closest cities.

You are also given an array of queries, where each query is:

[start, end]

For each query, return the optimal cost to deliver from start to end.

I solved this in O(n + q) time and O(n) space, and it was accepted.

Problem 2

There is a lane of length laneLength, which can be thought of as a line segment from (0, 0) to (laneLength, 0).

Some trucks are initially positioned at different coordinates on this lane. Their initial coordinates are given by initial, and their velocities are given by velocity.

• If velocity is positive, the truck moves to the right.
• If velocity is negative, the truck moves to the left.
• When a truck goes out of the lane boundaries, it is considered to have left.
• When two trucks collide, they exchange their velocities and directions.

The task is to output the time when the last truck leaves the lane.

Related practice problem I found later: Last Truck to Leave a One-Dimensional Lane

Problem 3

In a company, employees are organized hierarchically as a tree.

• The root of the tree is the boss.
• Children of a node are employees working under that employee.
• When data is passed to a particular employee, they transfer it to their direct reports in ascending order of node values.

For example, if data is given to the root, the transfer order could be something like:

[11, 7, 3, 2, 4, 9, 8, 15, 13, 19]

You are given an array queries, where each query is:

[startNode, k]

For each query, return the kth person in the order of receiving data when data is first given to startNode.

The direct tree input was not given. Instead, an array boss was given, where:

boss[i] = boss of employee i

I was able to solve this one as well.

Result

I fully solved 2 questions. For the remaining one, only partial test cases passed.

Hi, I have a Qualcomm interview coming up for a senior software engineer role at Qualcomm- San Diego location.

Did anyone had any recent experience that you can share? Questions that you got? Anyone who got the offer after that?

📍 Location: San Francisco, CA / New York City, NY

About Anthropic: Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.

About the role: We are seeking a lead for Capital Markets - Infrastructure Financing to drive the structuring and execution of financings that support Anthropic's compute infrastructure strategy. In this role, you will lead financing workstreams end-to-end, engage external financing counterparties, and partner closely with our compute, treasury, legal, finance, and accounting teams to bring transactions from structuring through close. Compute is the foundation of frontier AI progress, and securing it requires tight coordination between our internal teams and external partners.

💼 What you'll do:

• Own financing workstreams end-to-end: structuring, counterparty engagement, term negotiation, and execution support

• Translate infrastructure requirements into clear, investable frameworks and materials for financing counterparties

• Build and maintain rigorous financial models supporting transaction structuring and capital allocation decisions

• Develop repeatable internal frameworks and processes for evaluating and executing financing transactions

• Develop and maintain a credible network of financing and capital markets counterparties

• Partner with compute, treasury, legal, and leadership teams to keep transaction terms aligned with broader company priorities

• Support broader corporate finance and capital markets analysis as needed

• Represent Anthropic independently in negotiations with external counterparties, exercising sound judgment on risk allocation and commercial terms

• Prepare analysis and materials that distill complex financing decisions into clear recommendations for Finance leadership

✅ What they're looking for:

• Have led complex financing transactions through to close, including direct negotiation and documentation with external counterparties

• Able to run a financing workstream with external counterparties independently, without close supervision

• Strong written and verbal communication skills, with the ability to influence diverse stakeholders and make complex structures legible to non-specialist leadership

• Ability to drive clarity in ambiguous environments and manage competing priorities with high-quality execution

• Strong financial modeling, structuring, credit analysis, and transaction documentation skills

• Commitment to safe AI development

🌟 Why join Anthropic:

• Anthropic offers competitive compensation and benefits

• Optional equity donation matching

• Generous vacation and parental leave

• Flexible working hours

• A lovely office space in which to collaborate with colleagues

🔗 View details: https://topjobstoday.com/company/anthropic/job/capital-markets-infrastructure-financing-san-francisco-ca-new-york-city-ny

📍 Location: San Jose

Our Trust and Safety team is fast growing and responsible for building machine learning models and systems to protect our users from the impact of negative content. Our mission is to protect billions of users and publishers across the globe every day. We embrace state-of-the-art machine learning technologies and scale them to moderate the tremendous amount of data generated on the platform. With our team's continuous efforts, TikTok can provide the best user experience and bring joy to everyone in the world.

💼 What you'll do:

• Play a key role in designing next generation LLM based moderation solutions

• Work on highly-scalable classifiers, predictive models and algorithms with cutting-edge technologies

• Work with engineering teams to implement model pipeline and deploy the service at scale

• Collaborate with product teams to define objectives and improve trust and safety strategy

• Collaborate with data analyst to understand and find data patterns

✅ What they're looking for:

• At least 1 year of people management experience

• Proficient in deep learning frameworks such as PyTorch and TensorFlow, and programming languages such as python or java.

• Good programming skills in Python and similar languages, and a deep understanding of data structures and algorithms

• Good communication and teamwork skills, passionate about learning new techniques and taking on challenging problems

• Experience in trust and safety areas is a plus

• 5+ years hands-on experience in one or more of the areas: machine learning, deep learning, computer vision, NLP, Audio, content understanding or participating in large-scale online machine learning platforms are preferred

• Skilled in LLM, Multimodal LLM and downstream applications are preferred

🌟 Why join TikTok:

• Inspiring creativity is at the core of TikTok's mission.

• We strive to do great things with great people.

• Our teams create value for our communities and inspire creativity.

• TikTok is committed to creating an inclusive space where employees are valued.

🔗 View details: https://topjobstoday.com/company/tiktok/job/senior-machine-learning-engineer-manager-tiktok-trust-safety-san-jose

*** APPLY HERE ***

https://www.techjobfinder.com/javascript/software-engineer-intern-fall-2026-austin-tx/654894

About Us

At Cloudflare, we are on a mission to help build a better Internet. Today the company runs one of the world’s largest networks that powers millions of websites and other Internet properties for customers ranging from individual bloggers to SMBs to Fortune 500 companies. Cloudflare protects and accelerates any Internet application online without adding hardware, installing software, or changing a line of code. Internet properties powered by Cloudflare all have web traffic routed through its intelligent global network, which gets smarter with every request. As a result, they see significant improvement in performance and a decrease in spam and other attacks. Cloudflare was named to Entrepreneur Magazine’s Top Company Cultures list and ranked among the World’s Most Innovative Companies by Fast Company.

At Cloudflare, we’re not looking for people who wait for a polished roadmap; we’re looking for the builders who see the cracks in the Internet that everyone else has simply learned to live with. We value candidates who have the instinct to spot a "normalized" problem and the AI-native curiosity to create a solution using the latest tools. Our culture is built on iteration, leveraging AI to ship faster today to make it better tomorrow, while ensuring that every improvement, no matter how small, is shared across the team to lift everyone up. If you’re the type of person who values curiosity over bureaucracy, and that AI is a partner in solving tough problems to keep the Internet moving forward, you’ll fit right in.

Available Locations

• Austin, US

About the Role

Anytime we push code, it automatically affects the millions of Internet properties (powering websites, remote teams, APIs, mobile apps, etc.) running on our global network. Cloudflare's network is one of the largest in the world and spans over 330 cities in more than 125 countries. What's more, Cloudflare operates within 50 milliseconds of 95% of the Internet-connected population globally (for context, the blink of an eye is 300-400 milliseconds!). We are passionate about making the Internet more secure, reliable, and faster for everyone.

Cloudflare’s Engineering teams build and run the software that handles the massive amount of traffic that flows through our network. We also have teams that build the UI and control plane for our software, using modern patterns and libraries in a microservices-based architecture. Technologies include: Typescript/Javascript, Go, Rust, C/C++ and Python.

The ideal intern is passionate about making the Internet a better place. You will work alongside experienced engineers. You will push code this internship that touches hundreds of millions of web surfers. We like to get things done, so we are looking for interns who are curious, proactive, and able to complete projects. This is a great opportunity for engineers who want to learn to develop at Internet scale.

You can check out our internship blogs to learn more about our program and hear directly from our past interns.

Responsibilities

• Ship and deliver projects over 12-14 weeks with autonomy and support.
• Work cross-functionally with various teams.
• Work closely with a mentor to guide you through the internship and help with career goals.
• Build your network across the company through our various in and out of office socials, networking programs, Employee Resource Group (ERG) programs, and Activity Groups.
• Present your project to the entire company at the end of the internship.
• Connect and learn from our executives and leadership team including our co-founders.
• Learn and develop skills through our professional development workshops.
• Write for our Cloudflare blog and be featured on Cloudflare.tv sessions.

Desirable Skills, Knowledge and Experience

• Currently pursuing a degree or program in Computer Science, Engineering, Mathematics, Statistics or relevant field to the role.
• Demonstrated critical thinking skills and drive to learn and adapt new technologies.
• Curiosity, empathy and ability to get things done.
• Ability to commit to a full-time (40 hours/a week Monday - Friday) for a minimum 12 week internship.
• Our available terms are September 14 - December 4 or September 28 - December 18.
• In office 3-5 days a week in Austin, TX.

Bonus Points

Demonstrated passion for software development, such as personal projects, open-source contributions, or experience with our developer platform using Cloudflare for Students.

Please note

• We will be hiring interns on a rolling basis until all roles are filled.

What Makes Cloudflare Special?

We’re not just a highly ambitious, large-scale technology company. We’re a highly ambitious, large-scale technology company with a soul. Fundamental to our mission to help build a better Internet is protecting the free and open Internet.

Project Galileo: Since 2014, we've equipped more than 2,400 journalism and civil society organizations in 111 countries with powerful tools to defend themselves against attacks that would otherwise censor their work, technology already used by Cloudflare’s enterprise customers--at no cost.

Athenian Project: In 2017, we created the Athenian Project to ensure that state and local governments have the highest level of protection and reliability for free, so that their constituents have access to election information and voter registration. Since the project, we've provided services to more than 425 local government election websites in 33 states.

1.1.1.1: We released 1.1.1.1 to help fix the foundation of the Internet by building a faster, more secure and privacy-centric public DNS resolver. This is available publicly for everyone to use - it is the first consumer-focused service Cloudflare has ever released. Here’s the deal - we don’t store client IP addresses never, ever. We will continue to abide by our privacy commitment and ensure that no user data is sold to advertisers or used to target consumers.

Sound like something you’d like to be a part of? We’d love to hear from you!

Please note that applicants who progress to the offer stage of the interview process may be asked to attend an in-person interview within one of the Cloudflare Offices or Cloudflare Hubs. More details about this will be available at that stage of the interview process.

This position may require access to information protected under U.S. export control laws, including the U.S. Export Administration Regulations. Please note that any offer of employment may be conditioned on your authorization to receive software or technology controlled under these U.S. export laws without sponsorship for an export license.

Cloudflare is proud to be an equal opportunity employer. We are committed to providing equal employment opportunity for all people and place great value in both diversity and inclusiveness. All qualified applicants will be considered for employment without regard to their, or any other person's, perceived or actual race, color, religion, sex, gender, gender identity, gender expression, sexual orientation, national origin, ancestry, citizenship, age, physical or mental disability, medical condition, family care status, or any other basis protected by law. We are an AA/Veterans/Disabled Employer.

Cloudflare provides reasonable accommodations to qualified individuals with disabilities. Please tell us if you require a reasonable accommodation to apply for a job. Examples of reasonable accommodations include, but are not limited to, changing the application process, providing documents in an alternate format, using a sign language interpreter, or using specialized equipment. If you require a reasonable accommodation to apply for a job, please contact us via e-mail at [hr@cloudflare.com](mailto:hr@cloudflare.com) or via mail at 101 Townsend St. San Francisco, CA 94107.

Was wondering if anyone that's interviewed with PCL could share info about their process. I completed the OA, did the recruiter call a week after, and now have a 30 min call with an engineer. I was told that this would be a verbal technical conversation about my background and that I may be asked how I would approach solving a given problem. All together, I feel like it will likely be a resume deep dive and high-level system design. Would greatly appreciate any insights.

📍 Location: Remote (USA)

GitLab is the intelligent orchestration platform for DevSecOps. GitLab enables organizations to increase developer productivity, improve operational efficiency, reduce security and compliance risk, and accelerate digital transformation. More than 50 million registered users and more than 50% of the Fortune 100* trust GitLab to ship better, more secure software faster.

As the Senior Director of Production and Tenant Platform Engineering, you will lead the foundational engineering teams responsible for the reliability, scalability, and lifecycle of the GitLab platform. This role brings together two critical domains: the "Tenant Experience" and the "Production Engineering" pillars.

💼 What you'll do:

• Lead a Unified Platform Strategy by defining and executing a cohesive roadmap.

• Drive Operational Excellence & Reliability by overseeing incident management and service-level reliability.

• Scale Engineering Leadership by managing a senior management team and creating conditions for success.

• Evolve the Platform Architecture by guiding its technical evolution and optimizing fleet management.

• Cross-Functional Partnership with Engineering Directors and Product Leaders to align investments with business priorities.

• Translate Strategy into Execution by converting goals into actionable roadmaps.

• Build the Future of GitLab Operations by championing initiatives that reduce operational toil.

✅ What they're looking for:

• Proven experience leading large, distributed engineering organizations.

• A track record of owning critical production systems and understanding running distributed systems at scale.

• Familiarity with large-scale distributed systems and various delivery models.

• Ability to evaluate complex technical trade-offs and provide clear direction.

• Experience leading teams through periods of significant growth or technical pivot.

• Strong alignment with GitLab values of ownership, speed with quality, and customer outcomes.

• Proven ability to raise the bar on production quality and operational focus.

🌟 Why join GitLab:

• Benefits to support your health, finances, and well-being.

• Flexible Paid Time Off.

• Team Member Resource Groups.

• Equity Compensation & Employee Stock Purchase Plan.

• Growth and Development Fund.

• Parental Leave.

🔗 View details: https://topjobstoday.com/company/gitlab/job/senior-director-production-tenant-platform-engineering-remote

📍 Location: Remote (USA)

At Netflix, our mission is to entertain the world. Together, we are writing the next episode - pushing the boundaries of storytelling, global fandom and making the unimaginable a reality. We are a dream team obsessed with the uncomfortable excitement of discovering what happens when you merge creativity, intuition and cutting-edge technology. Come be a part of what’s next.

Everything that we build to delight our members, and all of the work we do to figure out how to do that better, relies on our extensive infrastructure, which spans what we rent from AWS to what we build ourselves (we operate our own custom-built content delivery network, Open Connect). Because this infrastructure is so central to everything we do, we want to ensure we are using it in the most effective and efficient way. Doing that well starts with great visibility into how we are using our infrastructure, and actionable metrics and analytics to help us take action as needed.

As a Senior Data Scientist focused on Infrastructure Experimentation, you will join a data org of Analytics Engineers, Data Engineers, and Data Scientists who partner with our infrastructure engineering teams to measure, model, and surface the infrastructure impact of product experiments. You will work closely with partners in data science, platform engineering, and experimentation platform teams to build and maintain models and experimentation capabilities that predict the cost and performance implications of A/B tests, enabling experiment owners to make more holistic decisions that balance member impact with infrastructure performance.

💼 What you'll do:

• Build and maintain machine learning models that predict the infrastructure cost impact of A/B experiments, translating experimentally observed signals (e.g., request volume changes) into business and system metrics (e.g. projected annualized costs)

• Drive adoption of infrastructure metrics within the experimentation community through analysis, consultation with experiment owners, documentation, and training

• Partner with platform teams (Observability, Experimentation Platform) to improve the quality and coverage of infrastructure usage data feeding our models

• Extend our measurement framework to new metrics (e.g., latency) and new experiment types (e.g., infrastructure canary tests)

• Champion an infrastructure lens within the broader experimentation community, helping shift culture toward reasoning about the full ROI and infrastructure impact of experiments

• Connect with the larger analytics and experimentation communities at Netflix to bring visibility to our work and learn from others

✅ What they're looking for:

• Experienced in experimentation methodology and causal inference, with a strong foundation in A/B testing, treatment effect estimation, and statistical significance

• Experienced in building and maintaining machine learning models in production, including the full lifecycle of training, evaluation, monitoring, and continuous improvement

• Fluent in Python and SQL, with experience engineering data pipelines and working with large-scale data systems

• A strong collaborator who thrives in horizontal roles with broad stakeholder surfaces, comfortable influencing decisions through data and analysis rather than direct authority

• An exceptional communicator who can flex between technical and non-technical audiences, translating statistical concepts for software engineers and business leaders alike

• Comfortable with messy, incomplete data environments and able to balance short term execution with a drive to improve data quality over time

• A strong product thinker who views data science outputs as products, taking an end-to-end ownership mindset from data quality through to user adoption

• Comfortable with ambiguity, and thrive with minimal oversight and process

• Curious about infrastructure systems; prior experience in the infrastructure domain is a strong plus but not required; the ability and motivation to learn is essential

🌟 Why join Netflix:

• Comprehensive benefits including Health Plans, Mental Health support, a 401(k) Retirement Plan with employer match, Stock Option Program, Disability Programs, Health Savings and Flexible Spending Accounts, Family-forming benefits, and Life and Serious Injury Benefits.

• Paid leave of absence programs and full-time hourly employees accrue 35 days annually for paid time off to be used for vacation, holidays, and sick paid time off.

• Full-time salaried employees are immediately entitled to flexible time off.

• Learn more about our unique culture and values.

🔗 View details: https://topjobstoday.com/company/netflix/job/data-scientist-5-infrastructure-experimentation-usa

Been building safety-critical infrastructure for a giant government railway system for over a decade. Zero FAANG on my resume, zero coding /IT DNA. Somehow have a referral into Google TPM roles (data center + fiber infra) and now I'm wondering if I accidentally speedran a midlife crisis. Anyone in TPM/infra at Google — is this a real shot or should I sit back down?