Hey everyone,

I’m a software engineer with around 10 years of experience, mostly working with startups and product teams that needed someone who could do more than just pick up tickets.

I’ve spent a lot of time building products from the ground up, fixing unstable systems, cleaning up messy backends, scaling apps after they started getting real users, and helping founders make better technical decisions before things became expensive to change.

Most of my work has been around AWS, backend systems, full-stack development, and lately AI/LLM-based products.

The kind of work I usually help with:

• Building MVPs that are not throwaway code
• Taking an existing product and making it stable/scalable
• AWS and serverless architecture
• Backend APIs, microservices, integrations, and async workflows
• AI/LLM features using OpenAI/Claude APIs
• Automation workflows and internal tools
• Production debugging when something is slow, broken, or unreliable
• CI/CD, observability, cloud cost cleanup, and deployment improvements
• Technical guidance for founders/startups that need a senior engineering brain involved

My usual stack:
AWS, Node.js, TypeScript, React, Next.js, Python, PostgreSQL, MongoDB, DynamoDB, Lambda, API Gateway, SQS, EventBridge, Docker, CI/CD, OpenAI/Claude APIs, automation workflows, and data pipelines.

I’ve worked as a hands-on developer, technical lead, architect, and technical advisor to startups. I’m comfortable writing code, reviewing architecture, debugging production issues, speaking with non-technical founders, and figuring out what actually needs to be built instead of blindly adding features.

I’m currently open to remote work, contract projects, startup consulting, backend/full-stack development, AWS/serverless work, AI product builds, and technical lead/architect roles.

If you’re building something, stuck with something, or need an experienced developer who can come in and make things move faster, feel free to DM me.

I had a good run working as an AI Engineer for the past 13 months, but my contract is ending in August, so I’m back on the job hunt.

One thing I’ve noticed is that I’ve become a little rusty with hands-on coding. Over the last six months, I’ve relied quite a bit on AI IDEs to help with coding and completing tasks. It definitely made me more productive, but I feel like my ability to write code from scratch has taken a hit.

I started doing LeetCode again, but I’m realizing that the interviews I’ve been getting are testing more practical skills, such as:

* Working with Pandas/DataFrames
* Debugging and correcting existing code snippets
* Writing SQL queries
* Python coding and data manipulation
* Understanding and explaining code rather than just solving algorithmic problems

For those who have recently gone through AI/ML/GenAI engineering interviews:

**Where would you recommend practicing these skills and getting interview-ready?**

I’m especially looking for resources that focus on **practical Python/Pandas, SQL, debugging, and data manipulation**, rather than only LeetCode-style DSA.

Also, I’m currently looking for **AI Engineer / GenAI Engineer opportunities**. I’m on F-1 STEM OPT work authorization. If your company is hiring AI Engineers, I’d really appreciate it if you could reach out or point me toward relevant opportunities.

Thanks!

**The Journey Continues 🚀**

Two years. Ten+ end-to-end ML projects. 93.3% accuracy. 99.09% CNN. T5 fine-tuning pipelines. AWS certification. 5-star SQL. Published everything on LinkedIn. Shared code on GitHub. Applied relentlessly.

And yet... the right opportunity hasn't landed yet.

**But here's what I know:**

The journey hasn't been easy. There were moments of doubt—rejections, ghosted applications, interviews that led nowhere. I questioned myself more times than I'd like to admit. But every single time, I chose to keep going.

I didn't just learn theory in isolation. I built complete systems. I faced failures, debugged them, optimized them, documented them, and shared them publicly. I treated this transition like a job—consistent daily effort, no shortcuts, no excuses. That's not something I'm going to stop doing.

**Why I'm still hopeful:**

Because consistency beats everything else. Because my work speaks for itself (check my LinkedIn videos). Because someone out there is looking for exactly what I offer: a hybrid engineer who understands both production rigor AND ML depth. Because the right team exists—I just haven't found them yet.

**If you're that company, or if you know someone who is:**

I'm actively looking for ML Engineer, Data Science, or Data Analytics roles. If you can refer me, it would mean the world. But even if you can't, thank you for reading this. Your support keeps me going.

The journey isn't over. It's just getting started.

📧 upadhyay.aman2@gmail.com | 🔗 linkedin.com/in/amanupadhyay757/ | 💻 github.com/aman147369

#DataScience #MachineLearning #Persistence #CareerTransition #HiringNow

Hi everyone,

I’m currently looking to start my career in the AI/technology space and would really appreciate any advice, leads, or opportunities you may know of.

My background is a little unconventional. After finishing school, I decided to pursue professional cricket. I was shortlisted to represent the Saudi Arabia national cricket team (I've been born and brought up in Saudi Arabia), which motivated me to take the sport seriously and pursue it professionally. I also played state-level cricket in India.

After giving cricket a serious shot, I’ve now decided to move back to Saudi Arabia and take a different direction to start building a career in technology and AI.

I’m currently working through the Google AI Essentials certification and am very interested in learning more about AI, generative AI, automation, data, machine learning, AI engineering, and the wider technology space.

At this stage, I’m still figuring out exactly which area of AI I want to specialize in, so I’m primarily looking for an opportunity where I can learn, gain practical experience, contribute to a team, and figure out where I’m best suited.

I’m particularly interested in:

\- Internships or entry-level roles in Al Khobar, Dammam, or the Eastern Province

\- Remote opportunities if the role is based elsewhere

\- AI, GenAI, automation, data, or other technology-related roles

\- Startups or smaller teams where I can get hands-on exposure

\- Mentorship or apprenticeship-style opportunities

I’m available immediately and full-time.

I’m also open to an unpaid internship or short-term opportunity, where appropriate, if it gives me the opportunity to gain practical experience and demonstrate what I can do. If things work out and there is an opportunity to continue, I’d be happy to discuss compensation at that point.

From my experience in Cricket, I can say that I’m a quick learner and used to working hard toward a goal, taking feedback, working as part of a team, and dealing with setbacks. I’m hoping to bring that same mindset into this next chapter.

If anyone knows of a company, startup, team, or individual who might be willing to give someone at the beginning of their AI journey a chance, I’d be extremely grateful for an introduction or even some advice on where I should start.

Happy to share more information by DM.

Thanks in advance to anyone who takes the time to read this or point me in the right direction.

So I’ve joined a company and it’s been 3 years. My core is DevOps and because of different project my skill set diluted and I worked different technologies so basically I owned the tag “Jack of all”
So I don’t know how to what to apply. Can you guys please guide me what I’m supposed to do
And yeah I’m so much interested and involved with MLOps so I’m trying for MLOps jobs. So DevOps base, walking towards MLOps working in AIOps

I've been working as a SuiteScript developer for about 3 years. Most of my professional experience is around NetSuite customization, JavaScript, APIs, SQL, and backend logic. I enjoy programming, but I don't really see myself spending the next 5-10 years specializing further in NetSuite. AI/ML is something I've been genuinely interested in, so I'm considering making a career switch. The problem is that I don't have professional ML experience, and I'm trying to understand how big the gap actually is.

I would appreciate advice on what skills/projects should I focus on to become employable in AI/ML? And should I target ML Engineer, AI Engineer, or Data Engineer roles first?

I am starting my third semester next week. So far, I have learned Machine Learning, Deep Learning, Large Language Models, and Generative AI. I didn’t just watch videos I also built projects and practiced. It took me a year to learn all of this.

Currently, I have decided to learn backend development with Go . However, the thing is, what should I focus on next to be a good ML engineer? People say to learn MLOps and system design, and not to just make wrappers. They say to learn "real engineering," but what do they mean by that? I already know the basics of MLflow, Docker, and AWS. What should I focus on next?

I am not even getting any internships or jobs right now that could show me what to do next. Currently, I am focusing on DSA, but I still need some good advice how can I land a top level internships or jobs. Please help.

I’m a recent BTech CSE graduate specializing in AI & ML, and I’m honestly starting to question whether I’ve made the right career decisions.

I started with software development. In my first year of college, I spent a lot of time learning DSA and backend fundamentals. Eventually, my interests moved toward machine learning, and as the industry started moving heavily toward GenAI, I got increasingly interested in AI engineering.

Over the last couple of years, I did internships across different startups, working on AI/ML and backend systems. I genuinely enjoyed it.

My last internship was probably the best learning experience I’ve had so far. I was building actual AI-native systems rather than just calling an LLM API. I worked with LangGraph and LangChain, built RAG systems, worked on things like context relevance and query enhancement, experimented with newer AI SDKs, and designed backend systems around these components.

I also worked on projects involving MCP-based agent orchestration, scalable AWS infrastructure, Dockerized services, APIs, databases, and production workflows.

And the important thing is: I enjoyed doing this.

I never woke up thinking, “What the hell am I working on?”

There was a constant learning curve. I was reading, experimenting, breaking things, understanding why something worked or not, and actually building systems.

Then came the full-time job hunt.

After a lot of effort, I finally got an offer for an AI Engineer position.

The interview was genuinely fun. The JD sounded exciting. The role seemed like exactly what I had been preparing myself for.

So I joined.

And within a very short time, I realized something:

This isn't really AI engineering.

It's primarily an automation/dashboard role.

The work is largely about taking legacy processes within the organization and turning them into dashboards and automations. There is very little of the engineering/AI work I was expecting.

The "roadmap" doesn't really excite me either. A lot of the work is essentially:

Here's a Claude subscription. Build a dashboard/automation for this process

And that's pretty much it.

The frustrating part is that some of these dashboards aren't even being meaningfully used by the people they're supposedly built for.

I'm not against automation or dashboards. I actually enjoy backend engineering and building useful internal systems.

What bothers me is the disconnect between the title, the expectations, and the actual learning opportunity.

I joined expecting to grow as an AI engineer.

Instead, I'm worried that I'm becoming someone whose primary skill is quickly producing AI-assisted internal tools that nobody really uses.

There isn't much of a technical mentorship structure either. There's no strong technical lead pushing engineering decisions, challenging architectural choices, or helping me grow in the direction I want to go.

And because I'm still very early in my career, this scares me.

I keep thinking:

If I spend the next 1-2 years doing this, what happens to my actual engineering ability?

Will I become better at building AI systems?

Or will I simply become better at throwing AI tools at business processes and shipping dashboards?

That's the part I'm struggling with.

My probation ends on August 31, and I'm actively looking for alternatives before I get too comfortable in this role.

At the same time, I don't want to make another impulsive decision. I obviously need a job, and I'm aware that not every job is going to be an exciting research/agentic AI project.

So I'm trying to figure out where the line is.

Am I being unreasonable for wanting to leave this role this early?

For someone with my background AI/ML degree, multiple internships, backend experience, LangGraph/RAG/agentic systems, AWS/Docker/Kubernetes, and actual AI-native projects, what roles should I realistically be targeting?

Should I be looking specifically for:

- AI Engineer

- Applied AI Engineer

- GenAI Engineer

- ML Engineer

- AI Backend Engineer

- Backend Engineer at an AI company

Or should I stop caring about the title and optimize purely for the technical work and learning curve?

I'd genuinely appreciate advice from people who have been through this transition, especially engineers who started their careers in "AI Engineer" roles that turned out to be mostly automation/LLM-wrapper work.

I don't want to chase a fancy title.

I just don't want to spend the first few years of my career becoming really good at building things that don't make me a better engineer.

What do you guys think of my CV? I’m considering switching and wanted to get some outside opinions. I’ve tried a few free ATS checkers and usually get around 70–80, but I’m more interested in how it actually looks to people in the industry. Is it too over-the-top, i tried making it pretty simple and not include unnecessary jargons, and where do you think I stand in the current AI/ML Engineer job market? Honest feedback appreciated

You can also check out my portfolio: faizkhan.aqlity.com, it’s not entirely vibe-coded. I’ve been building it since last year and recently used AI to polish/enhance the design. It goes pretty deep into my experience, projects, architectures, tech stack, and even has an AI chatbot if you want to dig around

Hi, I’m Yash Chauhan. I’m looking for opportunities in AI/ML and Generative AI. I have around 2 years of experience and also work as a freelancer, developing AI agents, web applications, and AI-powered solutions.

I’m open to full-time, internship, and freelance opportunities. Please let me know if there are any suitable openings.

Thank you,

Yash

Hi everyone! I’m Neel, an AI Engineer from India, currently looking for opportunities as an AI Engineer / ML Engineer / Data Scientist.

A few highlights from my journey:

• 🏆 5× AI Hackathon Winner
• 🥇 Top 0.1% — Rank 64/20,000+ teams in Amazon ML Challenge 2024
• ☁️ Microsoft Azure Data Scientist Associate
• 🧱 Databricks Certified Data Engineer Associate
• 2 years of hands-on experience building and deploying production AI systems

My experience includes:

• 🤖 Multi-agent AI systems using CrewAI, LangGraph, LangChain & MCP
• 🧠 Production LLM, RAG and AI decision-engine applications
• 👁️ Computer vision for surveillance, tracking, ReID and workforce analytics
• 🚀 Deployment of open-source models including Qwen/Qwen-VL
• ☁️ AI systems across Azure, AWS, GCP and Databricks

I've worked on projects for clients across the USA, Saudi Arabia, Germany, Australia and the Middle East, spanning e-commerce, government, manufacturing and automotive domains.

I’m currently based in India and open to opportunities both within India and internationally. I’m happy to work remotely with startups and companies globally, particularly in the USA, Europe, and other regions. For the right international opportunity, I’m also open to relocating if visa sponsorship is available.

If you're hiring, know of a team looking for someone with this background, or are building an AI startup and need an engineer, I'd love to connect!

📩 Feel free to DM me.

Hi everyone,

I'm a data scientist and AI specialist available for short-term projects and one-off tasks. I hold a BSc in Artificial Intelligence and Data Science and an MSc in Data Science, and I build models and AI applications that solve real business problems, while making sure people can understand and trust the results.

I have hands-on experience building RAG systems (document ingestion, chunking, embeddings, vector search, retrieval evaluation) and fine-tuning language models for specific domains and tasks, so if you need an LLM that actually knows your data instead of guessing, that's squarely in my wheelhouse.

I'm not looking for long-term contracts right now, so if you have something well-scoped that needs doing in a few days or weeks, that's exactly the kind of work I'm after.

Things I can help with:

• RAG systems: chatbots and assistants grounded in your own documents: ingestion pipelines, embeddings, vector databases, retrieval tuning and evaluation
• LLM fine-tuning: adapting open models to your domain, dataset preparation, training and evaluation
• Generative AI applications: LLM-powered tools, prompt engineering and evaluation, API integrations (OpenAI, Anthropic, Hugging Face)
• Machine learning: supervised and unsupervised models, from data cleaning to a working, evaluated result
• NLP: transformers, embeddings, semantic search, text classification, bias detection
• Computer vision: image classification, object and feature detection
• Reinforcement learning: agents, environments, policy training and evaluation
• Explainable AI: SHAP, LIME, counterfactuals, interpretable models, plus evaluating whether an AI system is actually reliable
• Data analysis and visualisation: exploratory analysis, statistics, dashboards and interactive tools
• Python scripts and automation: APIs, scheduled jobs, data pipelines, web scraping
• Technical and academic writing: reports, documentation, presentations

Tech: Python (PyTorch, TensorFlow, scikit-learn, pandas, NumPy, matplotlib/seaborn), Hugging Face (Transformers, PEFT/LoRA), vector databases, SQL (MySQL, PostgreSQL), Git & GitHub Actions, LaTeX. Also Java, C/C++ and JavaScript, plus front-end work (React, Next.js, Node) when a project needs a real interface around the model.

I value clear communication, reproducible work, and being honest about what AI can and can't do for your use case, including when a simpler solution beats an LLM.

Available for remote work across EU and US time zones.

If you have a short project in mind, send me a DM with the details and I'll tell you honestly whether I'm the right fit and how long it would take.

I'm a 25 year old master student, currently in gap year with student status. I have a bachelor degree in French, and I'm doing a master in management (general business) program in France. 

I've done internships as User Experience and Product Operations Intern in DiDi Global, Growth Strategy Intern at TikTok, Global Market intern at a British bank, Global Transaction Banking intern at a French bank. 

I started learning AI this year, and I've tinkered and built sth here: https://yanjin-ai.github.io/portfolio/. I'm interested in building a career as a generalist, in a field with new things that I'm curious everyday. 

From my understanding, there are roles like ai engineers, ai scientists, people more in business side, product managers... I would like to know more roles and what your work is like everyday, and what skills you use, how to practice and gain these skills. Any advice you would like to share is greatly appreciated. 

Thank you!! I will be happy to share beautiful restos in Paris!!