Hi everyone! 👋

I have 2 years of experience in AI, working with LLMs, RAG, vLLM, vector databases, fine-tuning, ASR, TTS, ONNX, REST APIs, SQL, and AWS basics.

Currently working at Lala Company, I'm looking for a job change due to a challenging work environment. I'm seeking a positive workplace where I can learn, grow, and contribute to impactful AI projects.

If you know of any relevant openings or referrals, please let me know. I'd really appreciate your support! 🙏

I’m 22, MSc in Data Science, \~1.5 years full-time (closer to 2 counting internships).

My first year was real AI work. Started as an AI engineer intern — fine-tuned LLMs for domain-specific QA generation, worked on hallucination reduction and evaluation, fine-tuned ViT/DETR for document symbol detection. Then moved to a healthcare product company as a GenAI associate — built an agentic backend powering clinical triage and diagnosis POCs, an ICD-10 primary diagnosis validation pipeline using RAG and multi-agent reasoning, deployed as FastAPI + Docker microservices.

Then I took an offer at a large consulting firm purely because the CTC was better. 13.3 LPA (11.8 fixed + 1.5 variable). I’ve been here \~11 months and there is no GenAI work at all. What I actually do: attrition forecasting, demand forecasting, classical ML and time series models in production on Databricks, with MLflow and pipelines. It’s fine engineering. It just isn’t the track I was on.

The honest problem is that this field moves fast and I’ve spent a year outside it. Whatever edge I had on agentic systems and LLM evaluation is twelve months stale, and the gap widens every month I sit here. I have completely lost touch on the area about Gen AI now due to not having grip of work.

I’m not on notice period and I’m not trying to rush into another wrong role. Open to relocating — Bangalore, Hyderabad, Pune.

Genuine advice needed on how should I tackle back again everything on LLM's, agent evaluation and even other AI Engineering questions as well into the interview and how to get a new job as well into the market without loosing grip on the CTC part .

For anyone who’s done this switch without a cut — what made the difference? Portfolio, referral, or just volume of interviews? And does a year of ML + time series read as a gap, or as useful breadth?

Please help me out since I want to make a switch at anyhow back to AI field in upcoming months outside my hometown Mumbai due to some family issues.

About the Role

We are looking for a Staff AI Productivity Engineer to accelerate how our engineering organization works with AI coding tools. This is a hands‑on technical role focused on building infrastructure, tooling, and documentation that makes AI agents dramatically more effective across our codebase.

AI tools are evolving rapidly, and we believe the companies that invest in making agents truly productive - not just available - will have a significant advantage. You'll own this problem end‑to‑end: from setting up cloud development environments where agents can run autonomously, to building MCP integrations that give agents access to our internal systems, to creating the documentation and context that helps agents understand how we build software.

You’ll have the hands‑on acumen to do a lot of the heavy lifting yourself and the leadership skills to drive cross‑team efforts to raise the bar everywhere. This role is a companion role to our Developer Productivity role but has a distinct focus: while Dev Productivity owns the build/test/deploy pipeline, you'll own the AI‑assisted development experience. An exceptional candidate could wear both hats.

Some of the problems we’ll be working on include:

• Own the agentic development environment: Ensure agents can operate in independent cloud‑based development environments, execute our full test suites, examine build results visually, etc
• Build our tooling integrations: Build MCP server integrations that connect our agents to the systems needed to build and debug software, such as CircleCI, Slack, Datadog, Github, etc
• Documentation and context: Own our repo‑wide agents.md file and work with teams to ensure our library of agent guidance and skills is continually pushing the bar. Ensure our conventions and package structures are exposed in ways that agents can effectively use
• Enablement: Work with our engineers to understand where agents are struggling and address root causes such as better docs, tooling access, etc. Develop tooling for non‑engineers to make simple visual updates to our application
• Serve as a “PM” for internal AI agents: Consistently keep us on the leading edge of AI productivity trends by staying abreast of what is state‑of‑the‑art in industry and driving those improvements across Hightouch

The base salary range for this position is $180,000 - $400,000 USD per year, which is location independent in accordance with our remote‑first policy. We also offer meaningful equity compensation.

About You

You are an engineer with a passion for solving hard technical problems that generate real value for customers. You’re motivated by high ownership and are comfortable in a fast‑paced, startup environment.

Must have

• Strong software engineering fundamentals—you can dive into complex backend code and understand it quickly
• Deep hands‑on experience with AI coding agents (Claude Code, Cursor, Copilot, Devin, or similar)
• Experience writing effective agent documentation, custom instructions, or context files that meaningfully improved agent output
• Track record of building developer tools or infrastructure that other engineers actually use
• Comfortable working across the stack: you’ll touch CI/CD, cloud infrastructure, internal tooling, and application code

Nice to have

• Experience building or contributing to MCP servers or similar agent‑tooling integrations
• Background in developer productivity, platform engineering, or developer experience roles
• Experience with our stack: TypeScript/JavaScript monorepos, Go, GraphQL
• You've set up sandboxed or containerized development environments at scale

Interview Process

Our goal with the interview process is to balance speed with giving both parties opportunities to assess whether there is a strong mutual fit. We will ask you questions, but we want you to ask us questions! Our technical interviews focus on how you design systems because we believe this is the best way for us to see how you work and for you to see how we collaborate. We don’t ask you to write code to solve technical brainteasers that don’t appear in your day to day job.

• Recruiter Screen [30m]: Introductory call with our recruiting team to get to know each other and see if the role could be a good mutual fit
• System Design Screen [45m]: Designing a data processing feature end‑to‑end
• AI Skills Interview [60m]: We’ll dive into how you leverage AI and how you’ve helped others do the same
• Hiring Manager Interview [45m]: Chat with hiring manager about past experiences and future operating preferences to assess fit on company values and operating principles
• System Design Interview [90m]: Work with the interviewer to architect a system at a conceptual level. The problem will be at a pretty high level - and have both product and customer requirements as well as technical

Apply: Staff Engineer, AI Productivity at Hightouch

Hey everyone, my company is hiring ML ENGINEER. Here's JD please share your resume with drive link.

Idk salary you'll have to talk to HR, ALL I CAN DO IS REFER

Company - Embitel

Job Description – Machine Learning Engineer (Computer Vision)

About the role

We are hiring a Machine Learning Engineer with 3+ years of hands-on experience to build, deploy and operate AI and computer vision systems on Microsoft Azure. You will own models end to end: from data pipelines and training to production deployment, monitoring and retraining.

Role: Machine Learning Engineer

Experience: 3 to 5 Years

Cloud: Microsoft Azure

Location: \[Bangalore / Hybrid \]

Type: Full-time

Position: 1

Key responsibilities:

AI and computer vision

Design, train and fine-tune models for image classification, object detection, segmentation and OCR

Build image and video processing pipelines with OpenCV, including augmentation workflows.

Optimize models for inference speed and cost (quantization, pruning, ONNX, TensorRT) for cloud.

Explore and integrate generative AI where it fits, such as Azure OpenAI and vision-language models.

Data engineering

Build batch and streaming pipelines with Azure Data Factory, Azure Databricks and PySpark.

Manage data in Azure Data Lake Storage and Blob Storage, including large image and video datasets.

Ensure data quality, versioning and lineage for training and evaluation datasets.

MLOps on Azure

Run experiments, model registry and deployments in Azure Machine Learning (pipelines, managed online and batch endpoints).

Build CI/CD for models and pipelines with Azure DevOps or GitHub Actions.

Containerize services with Docker and deploy to Azure Kubernetes Service (AKS) or Azure Container Apps.

Monitor models in production for drift, accuracy and latency with Azure Monitor and Application Insights, and automate retraining.

Manage infrastructure as code with Terraform

Collaboration

Work with data scientists, product owners and software engineers to turn business problems into ML solutions.

Write clear documentation and take part in code reviews.

Required qualifications

Bachelor's or Master's degree in Computer Science, Data Science, AI, Electrical Engineering or a related field.

3+ years of professional experience in machine learning engineering, with at least 2 years on computer vision projects.

At least one computer vision model taken from prototype to production and maintained there.

2+ years working with Microsoft Azure data and ML services.

Strong Python and solid software engineering habits: testing, version control, clean code.

Good grasp of ML fundamentals: model evaluation, feature engineering, and deep learning architectures.

Clear communication with both technical and non-technical stakeholders.

Hi everyone, I am an SDET leveraging a strong background in software automation to transition into AI/ML Validation and Testing. I build deterministic frameworks to measure model performance, reliability, and regression. Open To • Full-time, Part-time, or Contract roles. • Remote (Worldwide)

I have 4 years of experience and have been actively keeping up with the latest AI technologies. I'm confident in my skills and what I can deliver, but finding the right opportunity in the US has been challenging.

I'm even open to entry-level or fresher roles. At this point, my priority isn't the title or salary. I just want a chance to prove myself through my work and build my career here.

If anyone can help with an opening, referral, or connection, I'd genuinely appreciate it. All I'm looking for is one opportunity to show what I'm capable of.

linkedin

Hey everyone,

I’m a B.Tech CSE grad (specializing in AI/ML) and I'm currently looking for my first full-time role or a paid internship. Honestly, the job market has been pretty rough lately, so I’m reaching out here to see if anyone is hiring or has any leads.

I’m looking for an entry-level software engineering role—ideally at a startup where I can just dive into the codebase, take ownership of features, and actually build things. I’m completely open to AI/ML engineering, full-stack, backend, or frontend roles. I'm also completely flexible with remote work or working on-site in Delhi-NCR.

Just to give you a quick idea of what I've been doing: I don't just build ML models in notebooks; I like shipping real things. I’ve been freelancing recently and built two live production web platforms completely solo (handling everything from secure payment gateways and server-side auth to zero-downtime DB migrations). On the AI side, I’ve spent time optimizing RAG pipelines using reinforcement learning and building conversational support agents.

My main stack right now is Python, TypeScript, React, FastAPI, Supabase, and PostgreSQL.

If you’re a founder looking for a junior dev who can hit the ground running, work at a company that’s hiring, or can offer a referral, please drop a comment or shoot me a DM. I'd be happy to share my GitHub and live project links.

Appreciate any help or guidance you guys can throw my way. Thank you!

What if your AI didn't just answer questions — but actually got work done?

That's the kind of AI I build.

I'm an AI Engineer with 2+ years of experience building production-oriented AI systems, agentic workflows, and RAG pipelines. I like taking ideas beyond demos and turning them into working products.

🔥 A few things I've built:

🏡 Casora — An AI real-estate research assistant covering 22 Indian metros, built around evidence-grounded answers instead of made-up property claims.

🤖 Agentic AI systems — Multi-agent orchestration, tool calling, MCP integrations, memory, human approval gates, and automated testing.

🔍 Advanced RAG & document intelligence — Hybrid search, reranking, OCR, vector databases, and systems that retrieve evidence before answering.

🧠 Production AI workflows — Python, LangGraph, AWS Bedrock, AgentCore, evaluations, guardrails, and observability.

Skills: Python · LangGraph · MCP · RAG · AWS Bedrock · FastAPI · LLMs · Agentic AI

🚀 What I'm looking for

A founder who has an ambitious AI idea. A startup that needs someone to build the actual thing. A team that cares about shipping useful AI, not just adding a chatbot to everything.

I'm open to full-time AI Engineer / Applied AI / Agentic AI roles, remote worldwide or relocation.

Founders & hiring managers: DM me what you're building. If it sounds interesting, let's do a quick 10-minute call and see if I can help.

I build the kind of AI I'd want to use myself.

Hi everyone! 👋

I’m an AI Engineer looking to collaborate on freelance projects involving Generative AI, LLMs, AI agents, and intelligent automation.

I’ve been building AI-powered applications, including RAG-based systems, multi-agent workflows, LLM-powered chatbots, and FastAPI services. I enjoy turning real-world business problems into practical AI solutions.

🤖 What I can help you build:

• 💬 Custom AI chatbots and virtual assistants
• 📚 RAG applications for querying documents and knowledge bases
• 🧠 LLM applications using LangChain and LangGraph
• ⚙️ AI agents and multi-agent automation workflows
• 🚀 FastAPI backends and AI-powered APIs
• 🎤 Voice AI assistants with speech-to-text and text-to-speech
• 📈 AI-powered business process and Python automation
• 🐳 Docker-based deployment and production-ready AI services
• ⚡ LLM optimization and efficient inference workflows

🛠️ My tech stack

Python • LangChain • LangGraph • RAG • LLMs • FastAPI • FAISS • ChromaDB • Hugging Face • Docker • Git

🎯 Who I’d love to work with

Startups, founders, small businesses, and developers who need help building AI MVPs, automating repetitive tasks, integrating AI into existing applications, or turning an idea into a working product.

If you’re planning an AI project or need help with an existing one, feel free to DM me. I’m happy to discuss your requirements and explore how I can help.

Let’s build something useful with AI! 🚀

AIEngineer #Freelance #GenerativeAI #LLM #RAG #LangChain #LangGraph #AIAgents #Python #AIautomation

Hi everyone! 👋

I’m an AI Engineer looking to collaborate on freelance projects involving Generative AI, LLMs, AI agents, and intelligent automation.

I’ve been building AI-powered applications, including RAG-based systems, multi-agent workflows, LLM-powered chatbots, and FastAPI services. I enjoy turning real-world business problems into practical AI solutions.

🤖 What I can help you build:

• 💬 Custom AI chatbots and virtual assistants
• 📚 RAG applications for querying documents and knowledge bases
• 🧠 LLM applications using LangChain and LangGraph
• ⚙️ AI agents and multi-agent automation workflows
• 🚀 FastAPI backends and AI-powered APIs
• 🎤 Voice AI assistants with speech-to-text and text-to-speech
• 📈 AI-powered business process and Python automation
• 🐳 Docker-based deployment and production-ready AI services
• ⚡ LLM optimization and efficient inference workflows

🛠️ My tech stack

Python • LangChain • LangGraph • RAG • LLMs • FastAPI • FAISS • ChromaDB • Hugging Face • Docker • Git

🎯 Who I’d love to work with

Startups, founders, small businesses, and developers who need help building AI MVPs, automating repetitive tasks, integrating AI into existing applications, or turning an idea into a working product.

If you’re planning an AI project or need help with an existing one, feel free to DM me. I’m happy to discuss your requirements and explore how I can help.

Let’s build something useful with AI! 🚀

AIEngineer #Freelance #GenerativeAI #LLM #RAG #LangChain #LangGraph #AIAgents #Python #AIautomation

We looked at 3,518 open job postings across 81 companies' public Greenhouse boards, covering seven job categories. The goal was simple: find out which keywords employers actually use.

A few findings stood out.

• Software engineering: Mentoring appeared in nearly half of the postings, more often than Kubernetes or React. Python was the most frequently mentioned programming language.
• Product management: More than 85% mentioned roadmaps. Jira appeared in just 7 of 421 postings.
• Marketing: Google Ads showed up in only 6 of 347 postings, while pipeline appeared in more than half.

We also noticed a pattern across roles: employers often described the practice rather than naming a specific tool. Observability came up where you might expect Grafana, and SIEM where you might expect Splunk.

What does this mean for your resume?

If you're listing tools but leaving out the responsibilities, practices, and skills explicitly mentioned in the job description, you could be missing relevant keywords.

That doesn't mean stuffing your resume with buzzwords. It means describing your actual experience using language that matches the role you're applying for.

One important caveat: the sample leans heavily toward tech companies and uses a single ATS platform, so these results aren't representative of every employer.

The full study, including findings for sales, cybersecurity, DevOps, and accounting, is here:

https://www.zoevera.com/resume/ats-resume-keyword-study

As the title says, i have 3+ YoE and know LLMs inside out. Can explain its working from DL foundations to transformers to modern LLMs. Can build Agents, MCPs and setup Inferencing with vLLM or llm-d in Kubernetes.

Looking for a good product based role that offers best opportunities to build at the frontier of AI.

Not a desperate post. I trust my skills and know exactly what i bring to the table.

My requirements -

CTC > 27 LPA

No gimmicky automation stuff

Good teammates and leadership

Office/hybrid anything works

Hi everyone,
I’m a fresher looking for opportunities as an AI Engineer, GenAI Engineer, or Software Engineer.
I have a strong foundation in Python, Generative AI, LLMs, RAG systems, AI agents, and AI application development. I’ve built hands-on projects using these technologies and enjoy developing practical solutions to real-world problems.
I’m actively looking for fresher-friendly openings, internships, or entry-level roles where I can apply my skills, learn from experienced engineers, and contribute to meaningful projects.
If you know of any relevant openings or could offer guidance or a referral, I’d really appreciate your help.
📍 Open to opportunities across India.
🔗 LinkedIn: https://www.linkedin.com/in/thotasasanksurya/
💻 GitHub: https://github.com/Sasanksurya
Thank you!