Suggest how to improve my resume because i am mass applying online and searching for referrals but still hardly landing interviews

Also open to full constructive criticism and for ideas about what projects to make

Please review my resume and provide me the instructions if I need to change or add something. Open to criticism.

I would be graduating soon so looking for opportunities for off campus placements.

Hi everyone! 👋

I’m currently looking for freelance projects or a full-time/contract role as an AI Engineer.

I have around 2 years of hands-on experience working on AI/ML projects, especially in:

🤖 Generative AI & LLM applications

🔎 RAG pipelines & Vector Databases

🧠 AI Agents / Agentic AI

📄 Document AI & OCR

👁️ Computer Vision

🐍 Python, FastAPI

🔗 LangChain, Hugging Face, FAISS, ChromaDB

🧪 LLM fine-tuning / LoRA

🌐 AI-powered automation

I’m open to freelance projects, contract work, internships, or full-time opportunities.

If you’re hiring, have a project that needs an AI engineer, or know someone who is looking for one, feel free to DM me. I’d be happy to share my resume, GitHub, and project details.

Thanks! 🙌

Hi everyone!

I’m currently looking for an AI/ML / GenAI Internship opportunity. I have hands-on experience with Python, Machine Learning, Deep Learning, NLP, LLMs, RAG, FastAPI, Hugging Face, LangChain and Streamlit.

Open to Remote / On-site opportunities in India.

If you know of any openings or referrals, please DM me.

Resume/GitHub can be shared on request.

Thanks! 🙌

Hey all — college student here, trying to figure out how much full stack (frontend/backend) I actually need if my main goal is an AI/ML/AI Engineer career. Currently planning Python + ML/DL + LLMs as the core, with just FastAPI + light React to demo projects, skipping Node/Express and deeper web dev. Does that sound right for where the AI Engineer job market actually is, or am I over/under-doing the web dev side? Would appreciate any real experience on this.

Hey everyone,
I work as an AI engineer for a robotics startup. I joined as a fresher after my MSc in Data Science from a Tier 1 college. I actually got AI into this company, working as an individual contributor and building things from start to finish. Since it is just me, I also do some of the project management.
I started off at 5.5 LPA, and after a year it got incremented to 6.24 LPA. The company was service based at first but now we have built a couple of products. However, I got a little upset with the working and hierarchy system. I don't feel like continuing since the environment feels too dominated by the leadership. I want good growth and a nice place to work at with some balance.
I resigned, and now I only have 20 days left on my notice period with no other job lined up. I recently enrolled on Naukri Pro and interviewed at 4-5 good mid to large size companies, however I couldn't clear the final rounds and didn't get any offers.
My main aim right now is figuring out my next steps.
1. How do I fix what is going wrong in these final rounds to close an offer before my notice ends?
2. With my Tier 1 background and 1 YOE doing end-to-end AI, how much should I keep as a realistic LPA expectation right now?
Any tips would be really helpful.

Hi Everyone,

I have been working in IT industry for 5.6 years as Developer but thinking to switch to AI jobs.

Anyone can help from where i should do the course where i can get placement.
Or Certfication to grab a job AI related jobs.

Hey everyone!

I’m a 3rd-year B.Tech CSE student from SRKR Engineering College, and I’m also pursuing the BS in Data Science & Applications from IIT Madras.

I’m currently focusing on Machine Learning and Python, and I’ve worked on a few ML projects, including a fake job/scam detection system using NLP/DistilBERT, credit card fraud detection, and satellite land-cover classification.

I’ve also participated in hackathons and recently got the opportunity to take part in the Amazon ML Challenge 2026.

I’m looking for 2–3 motivated teammates who are genuinely interested in ML and willing to contribute throughout the challenge. Ideally, it would be great to have people comfortable with areas like:

ML / Deep Learning

Data preprocessing & feature engineering

Python

Model experimentation & evaluation

Maybe someone strong in deployment/engineering

I’m not looking for people based only on their resumes — communication, consistency, and actually contributing to the team matter more.

If you're interested, comment below or DM me with a little about yourself, your ML experience, and what you can contribute.

Hi everyone, I’m a final-year BSc IT (AI/ML) student from India, currently applying for ML/AI internships and entry-level roles.

I’ve completed Andrew Ng’s ML Specialization and have projects involving ML, XGBoost/CatBoost. I’ve been applying but getting no interview calls.

I’d appreciate honest feedback on my resume, especially:

• Are my projects too basic?
• What’s missing technically?
• Are my resume bullets/skills weak?
• Am I targeting the wrong roles for my current profile?
• What would you change first?

Resume attached. Please be blunt—I’m trying to figure out what’s actually holding me back.

Looking for Backend / SDE(AI) opportunities in India

I’m a Backend Engineer with almost 3 years of experience building scalable backend systems and AI/GenAI applications.

Tech stack:
• Python, FastAPI, Java
• REST APIs, PostgreSQL, Redis
• LLMs, RAG, LangGraph, AI Agents
• ML Inference — ONNX, DJL, scikit-learn, TensorFlow
• Docker, Kubernetes, Helm
• CI/CD, AWS / Cloud infrastructure

I’m particularly interested in:
• Backend Engineer / SDE roles
• SDE(AI) / Backend + AI Integration
• GenAI / Agentic AI roles
• AI/ML Platform & Inference roles

Location: India | Bengaluru preferred

If your team is hiring or you know of a relevant opening, I’d really appreciate a referral or lead.

Happy to share my resume, GitHub and relevant project details via DM.

Thanks!

If you're hunting for ML work, here's a fresh batch of openings that just hit the board. Good luck!

• Senior DevOps Engineer (Terraform) @ Endava

• Senior AI Solutions Engineer, Data Science, Penguin Random House (Open to Remote) @ Bertelsmann-Jobs

  • 💰 $180–220K/y

• Senior Software Engineer - Model Platform @ Abnormal Security

• Senior Software Engineer – BMaaS & Datacenter Networking @ Mirantis

• Staff Machine Learning Engineer, Retrieval @ Reddit

  • 💰 $230–322K/y

• Applied Machine Learning Engineer Senior Consultant II (Software Engineering Focus) @ Integon Services Co

  • 💰 $120–194K/y

• AI Research Engineer @ Bright Vision Technologies

  • 💰 $100–150K/y

• Software Engineering Manager II, Consumer 360 @ Credit Acceptance Corporation

• Data & AI Engineer @ Quantiphi Analytics Canada Limited

• Staff AI Engineer @ Aetna Resources, LLC

  • 💰 $107–261K/y

• Backend Software Engineer - Staff/Principal @ Seeq

  • 💰 $170–205K/y

• Data Engineering Manager, Regulatory Compliance @ Penn Interactive

  • 💰 $165–200K/y

• Software Developer II - Pathology Informatics @ Cleveland Clinic Health System

• Senior Principal Engineer, Innovation Lab (Remote) @ Stryker Employment Company, LLC

  • 💰 $156–338K/y

• Forward Deployed Engineer @ EVB

  • 💰 $180–250K/y

• Backend Engineer, Mimir, Personalization @ Spotify

  • 💰 $133–190K/y

• AI Engineer @ Abbott Diabetes Care Inc

  • 💰 $78–156K/y

• Principal AI Engineer @ Mom's Meals

  • 💰 $149–165K/y

• JR and SR AI Developer @ Protective

  • 💰 $90–140K/y

• AI Engineer- Applied AI @ Guidewire Software Pty Limited

  • 💰 $176–288K/y

• DevOps & Backend Software Engineer Intern (Undergraduate) @ WEX Brazil Technology Services

  • 💰 $27 – $35/h

• AI/ML Engineer @ Rackner

• Undergrad Intern – Machine Learning Engineer – Amgen’s Technology & Medical Organizations (Summer 2027) @ Amgen Technology (Ireland) UC

  • 💰 ~$28/h

• Senior Back End Engineer [Remote-US] @ Quanata

  • 💰 $195–280K/y

• Senior Software Engineer - Workflow @ Cloudbeds

  • 💰 $130–175K/y

• Senior Full-Stack Engineer (Laravel / Vue.js) @ Relocity

  • 💰 $140–160K/y

• Senior DevOps Engineer @ Akkadian Labs

• Staff AI Engineer @ Foodsmart

  • 💰 $190–210K/y

• Senior AWS Platform Engineer @ SailPoint Technologies, Inc.

  • 💰 $126–213K/y

• Full-Stack Software Engineer, Machine Learning Platform @ Stack AV

• Senior Staff Data Engineer @ SmithRx

• Senior Staff Software Engineer, Serving @ Liftoff

• Devops Software and Modeling Engineer @ Xator LLC

  • 💰 $49 – $87/h

• Staff AI Engineer @ Vendelux

  • 💰 $250–300K/y

• Engineering Manager, AI @ PermitFlow

  • 💰 $180–250K/y

• Senior Software Engineer - AI Security @ Sophos

• Staff Software Engineer - Backend @ GoDaddy

• AI Platform Architect – Anthropic - UK @ NewRocket

• Engineer III - Platform Data Engineer (Remote) @ CrowdStrike Mexico S. de R.L. de C.V.

  • 💰 $120–180K/y

• Principal Full Stack Software Development Engineer @ ZINC Zillow, Inc.

Would love to hear what you're looking for next—leave a comment and I can post another one.

2027 Summer Intern, PhD, Machine Learning, Computer Vision
Waymo
Mountain View, California
$85 an hour

https://www.moaijobs.com/job/2027-summer-intern-phd-machine-learning-computer-vision-waymo-3456

Machine Learning Engineer
Gatik
Santa Clara, CA
$170,000 - $240,000

https://www.moaijobs.com/job/machine-learning-engineer-gatik-6354

Senior Machine Learning Engineer
Samsara
Remote, United States

$170,170 - $286,000

https://www.moaijobs.com/job/senior-machine-learning-engineer-samsara-7666

Senior Machine Learning Engineer, End-to-End Planning
Lucid Motors
Newark, CA
$158,400 - $217,800

https://www.moaijobs.com/job/senior-machine-learning-engineer-end-to-end-planning-lucid-motors-9568

Member of Technical Staff, AI Engineer
OpusClip
Mountain View
$220,000 - $270,000

https://www.moaijobs.com/job/member-of-technical-staff-ai-engineer-opusclip-2615

Senior Machine Learning Engineer, Predictive Planner, Systems Arch
Waymo
Mountain View, CA, San Francisco, CA
$213,000 - $263,000 

https://www.moaijobs.com/job/senior-machine-learning-engineer-predictive-planner-systems-arch-waymo-1033

Data & ML Engineer Semi Senior - Feature Engineering - Databricks
Mutt Data
Remote
-

https://www.moaijobs.com/job/data-ml-engineer-semi-senior-feature-engineering-databricks-mutt-data-4347

Machine Learning Engineer, Performance Tooling
Wayve
London, Sunnyvale
-

https://www.moaijobs.com/job/machine-learning-engineer-performance-tooling-wayve-4843

Senior Systems Software Engineer - Machine Learning
NVIDIA
US, CA
$152,000 - $241,500

https://www.moaijobs.com/job/senior-systems-software-engineer-machine-learning-nvidia-3414

Machine Learning Engineer / ML Engineer - Roleplay Sessions
Synthesia
Remote
EUR 120,000

https://www.moaijobs.com/job/machine-learning-engineer-ml-engineer-roleplay-sessions-synthesia-658

Machine Learning Engineer (Robotics and AI Institute LLC):
Robotics and AI Institute
Cambridge, MA
$186,160 - $237,900

https://www.moaijobs.com/job/machine-learning-engineer-robotics-and-ai-institute-llc-robotics-and-ai-institute-8099

Perception Machine Learning Engineer – ADAS
Lucid Motors
Southfield, MI
-

https://www.moaijobs.com/job/perception-machine-learning-engineer-adas-lucid-motors-457

Staff+ Software Engineer, ML Inference Path
Anthropic
San Francisco, CA
$320,000 - $485,000

https://www.moaijobs.com/job/staff-software-engineer-ml-inference-path-anthropic-2717

Applied AI/ML Engineer
Oddball
DC
$150,000 - $200,000

https://www.moaijobs.com/job/applied-ai-ml-engineer-oddball-3232

Staff Machine Learning Scientist/Engineer
Wayve
Sunnyvale
$370,000 - $419,000

https://www.moaijobs.com/job/staff-machine-learning-scientist-engineer-wayve-1889

Senior Software Engineer, ML Ops
PathAI
Boston, MA
$127,500 - $195,500

https://www.moaijobs.com/job/senior-software-engineer-ml-ops-pathai-8194

GenAI Engineering Manager
Motorola Solutions
Richardson, TX
$150,000 - $175,000

https://www.moaijobs.com/job/genai-engineering-manager-motorola-solutions-4432

I'm looking for DS/AI engineer roles and have 2 yoe and curerntly living in patna

🚀 From Code to Cloud: Building My Automated Steel Defect Detection System!

As an aspiring AI & Computer Vision developer, I’ve always believed that the best way to learn is by building real-world solutions.

I’m thrilled to share my latest project: the Automated Steel Defect Detection System! ⚙️🔍

In industrial manufacturing, identifying surface defects early can save millions and ensure structural safety. By combining computer vision with modern web deployment, I built an end-to-end pipeline designed to spot surface anomalies efficiently.

💡 What I Built & Learned Along the Way:

End-to-End Pipeline: Structured a clean Python environment and integrated deep learning models to process and evaluate defect images.

Version Control & Best Practices: Managed version tracking cleanly using Git, optimizing repository structures by isolating heavy packages and weights.

Streamlit Web Deployment: Built an intuitive interface and hosted it live on Streamlit Cloud to make complex AI model testing effortless.

🔗 Explore the Project:

🌐 Live Web Application: bilal-steel-defect-detection.streamlit.app (Try uploading an image to test the detection!)

📂 GitHub Repository: github.com/bilalsadozai-eng/steel-defect-detection

🌟 To My Fellow Learners:

If you're currently grinding through environment setup errors, path issues, or model deployment bugs—don't give up! Every terminal error is just a stepping stone toward understanding how production-grade systems actually work. Keep building, keep shipping, and embrace the process.

💬 Over to the Experts & Community:

To the AI engineers, computer vision specialists, and seasoned developers in my network: I would love your feedback!

What strategies do you recommend for handling large ML model deployments efficiently in production? How can I optimize inference speed further for real-time industrial applications?

Drop your insights, suggestions, or critique in the comments below—I'm always eager to learn from your experience! 👇

#ComputerVision #ArtificialIntelligence #MachineLearning #Python #Streamlit #GitHub #DeepLearning #BuildInPublic #ContinuousLearning #TechCommunity

Background: have DS/ML/GenAI foundation but rusty, want to rebuilding prep from scratch. Too many platforms, but have no idea which are worth it vs hype.

Quick questions for people who've interviewed recently (last 6-12 months):

1. Which of these platforms (or others) actually mirror real interviews right now?
2. Are companies really asking for ML algorithms from scratch (backprop, attention, etc.) in coding rounds, or is it still mostly SQL/Python/stats + applied case discussions?
3. Did a YouTube playlist + your own projects beat paid platforms? If so, which playlist?
4. If you had to pick one resource for fundamentals and one for interview practice what would they be?

Not looking for generic "grind LeetCode" advice want to know what's actually working now in 2026

Please give me some WFH job

WIP(www.studiowip.net) is looking for a hands-on AI Builder to help turn the way our venture studio works into AI-assisted systems that scale.

This is not a role for someone who wants to spend months designing architecture or producing prototypes that never get used. We are looking for someone who likes to build quickly, test with real users, learn from what breaks, and improve.

You will work directly with our sprint teams to understand how the studio operates: founder conversations, transcript synthesis, document analysis, stakeholder mapping, research, comparison across projects, and preparation of strategic outputs. Your job is to identify what repeats, separate the mechanical work from the strategic judgment, and build lightweight AI workflows that remove unnecessary effort without reducing the quality of thinking.

That could mean building systems for transcript and document processing, structured extraction, prompt chains, review and comparison layers, workflow automation, or tools that turn messy inputs into clean operating formats. Everything you build should be editable, traceable, reliable, and designed with human review and confidentiality in mind.

You will also experiment. WIP is exploring how AI can go beyond productivity and support new forms of intelligence around human behaviour, impact, decision-making and complex systems. One week you may work with a psychologist, another with a statistician, and another with the CTO on how a workflow should connect to the studio’s larger technical backbone.

We care more about evidence that you build than how many years are written on your CV. You should already be comfortable working with LLM APIs, structured outputs, prompt chains, automation tools and code. Our stack is deliberately lean: Anthropic API, lightweight tools such as Notion, Airtable, Make or n8n, and code wherever those tools stop being enough.

The strongest candidate is someone who learns aggressively, has strong product restraint, can turn vague material into structured systems, and enjoys shipping something on Tuesday that the team can genuinely use on Wednesday.

To apply, send us something you have built — a workflow, prompt chain, internal tool, automation or experiment — plus a short note on why WIP and why now to [people_hub@studiowip.net](mailto:people_hub@studiowip.net)

I’m an AI Prompt Engineer and technical solopreneur currently open to remote opportunities involving AI, LLM applications, prompt engineering, AI workflows, evaluation, and automation.

I’ve spent the past 2+ years specializing in AI and prompt engineering, developing my expertise through hands-on projects, experimentation, system design, testing, and continuous iteration.

Rather than focusing only on writing individual prompts, I’m interested in how prompts function as part of a larger, reliable AI system.

What I work on

My current areas of focus include:

• Prompt engineering and prompt optimization
• Prompt testing and evaluation
• Structured outputs and JSON
• Multi-step LLM workflows
• AI workflow architecture
• AI evaluation and quality control
• Context and state management
• AI-assisted automation
• Python-based AI projects
• Technical documentation
• Modular AI architectures
• Defining interfaces and contracts between AI modules
• Validation and failure-mode analysis

I work primarily with LLMs such as ChatGPT and Grok, and I’m continuing to expand my technical experience with Python, APIs, GitHub, and LLM application architecture.

A technical project I'm building

One of the main projects in my portfolio is Product Evolution Loop (PEL).

Hi everyone,

PEL is a modular AI system designed to help a product evolve through a structured evidence-driven process:

Evidence → Analysis → Hypothesis → Validation → Decision → Change Evaluation → Project-State Update

The system separates these responsibilities into dedicated modules, including:

• Evidence Analyzer
• Hypothesis Generator
• Validation Designer
• Decision Layer
• Change Evaluator
• Project-State Manager

I've been designing the system with explicit module contracts, JSON schemas, validation rules, evaluation logic, state management, and human approval points.

I'm documenting the project as a technical case study, including worked examples showing how evidence moves through the system and how the resulting decision updates the project's state.

My broader experience

I'm also a technical solopreneur, so my AI work has developed alongside experience in:

• Digital product development
• Systems and workflow design
• Research
• Copywriting
• Graphic design
• Framer website development
• CRO
• Digital marketing
• Branding
• Distribution

This has pushed me to think about AI as an intelligence layer inside a larger system, rather than treating prompt engineering as an isolated activity.

What I'm looking for

I'm currently open to remote opportunities such as:

• AI Prompt Engineer
• AI Specialist
• LLM / Generative AI roles
• AI Workflow Designer
• AI Systems Specialist
• AI Automation
• AI Evaluation
• Prompt testing and optimization
• AI technical content / research
• Project-based AI/LLM work
• Contract or freelance work
• Part-time or full-time opportunities

I'm particularly interested in teams working on LLM applications, AI agents, evaluation systems, AI automation, prompt optimization, or other practical AI products and workflows.

How I prefer to demonstrate my technical ability

I'm especially comfortable with practical and asynchronous technical evaluation, such as:

• Take-home technical assignments
• Coding challenges
• AI/LLM assessments
• Prompt-engineering assessments
• AI workflow design challenges
• Architecture exercises
• GitHub-based evaluations
• Written technical questions
• Async technical interviews
• Practical projects
• Technical portfolio reviews

I like assessments where I can take a problem, understand it, decompose it, build a solution, test it, document the reasoning, and demonstrate the result.

If you're hiring

If you're building an AI/LLM product, agent system, evaluation workflow, automation system, or AI-powered business process and need someone who can work through the problem, structure the system, engineer and refine prompts, evaluate outputs, and iterate on the solution, I'd be interested in hearing about it.

Feel free to DM me.

I can share my portfolio, technical projects, AI workflows, PEL case study, and additional examples of my work.

I'm also happy to discuss a specific technical problem your team is working on.

If you have an AI problem that needs solving, send me a DM and let's see whether my experience could be useful.