We are hiring a Senior AI/ML & Data Engineer to join our team full-time and work on long-term projects.

Role Overview
You will design, build, and deploy data pipelines and machine learning systems, taking models from experimentation to reliable production use.

Requirements

• 5+ years of professional experience in data engineering, machine learning engineering, or a closely related field
• Strong programming skills in Python and SQL; experience with at least one of Java, Scala, Go, or TypeScript is a plus
• Hands-on experience building and maintaining data pipelines (batch and/or streaming) using tools such as Airflow, dbt, Spark, or Kafka
• Experience with data warehouses and lakes (Snowflake, BigQuery, Redshift, Databricks, or similar)
• Experience training, evaluating, and deploying ML models using frameworks such as PyTorch, TensorFlow, or scikit-learn
• Experience with cloud platforms (AWS, GCP, or Azure), Docker, and CI/CD
• Strong understanding of data modeling, system design, testing, and production deployments

Nice to Have

• Experience with LLMs, RAG, vector databases, and AI agents
• Experience with MLOps tools (MLflow, Kubeflow, SageMaker, Vertex AI)
• Infrastructure as Code experience (Terraform)
• Experience building APIs to serve models (FastAPI, Flask)
• Experience with monitoring, observability, and data quality frameworks

Tech Focus

• Data Engineering: Python, SQL, Spark, Airflow, dbt, Kafka
• AI/ML: LLMs, RAG, ML pipelines, model deployment, MLOps
• Cloud & Infrastructure: AWS/GCP/Azure, Docker, CI/CD, Terraform

Details

• Remote, full-time, long-term position
• Compensation: $60,000-$72,000/year

How to Apply
Please send me a direct message with:

1. Your resume
2. Your LinkedIn and/or GitHub profile
3. A brief summary of your recent experience, including one or two data or ML projects you’ve taken to production

We look forward to hearing from you.

We're Hiring: Senior AI / LLM Engineer (GenAI Systems)

Location: Lahore ON SITE

Salary: $2,000 - $2,300 USD per month ( Open to further negotiations for the right talent )

Language Requirement: Strong English Communication Skills

Wigiwork is building a next-generation AI infrastructure platform focused on LLMs, intelligent matching systems, and scalable AI products. We're looking for a Senior AI / LLM Engineer who can help architect, build, and deploy production-grade AI solutions while providing technical leadership to a growing team of AI engineers.

What You'll Do

Build, deploy, and scale end-to-end AI and machine learning pipelines.

Design and implement LLM-powered applications and services.

Develop Retrieval-Augmented Generation (RAG) systems and AI agent workflows.

Optimize model inference, performance, and operational efficiency.

Improve prompt engineering strategies, NLP workflows, and data quality processes.

Create structured output systems, function-calling workflows, and model integrations.

Lead and mentor a small team of Junior AI Engineers through code reviews, technical guidance, and best practices.

Required Skills & Experience

We value deep expertise over checking every box.

Software Engineering

Python development

APIs and system integrations

Git and version control

CI/CD pipelines

Containers (Docker)

Databases and backend architecture

AI & Machine Learning

PyTorch, TensorFlow, or Keras

LLM application development

Prompt engineering

Vector databases and embeddings

LangChain or similar AI frameworks

RAG architecture and implementation

What We're Looking For

Proven experience building and deploying AI, ML, or LLM systems in production environments.

Strong understanding of transformer-based architectures and modern AI frameworks.

Ability to work across infrastructure, models, and product development.

Strong problem-solving mindset with a focus on delivering real-world solutions.

Leadership experience or the ability to mentor and guide junior engineers.

Nice to Have

NLP, classification, NER, semantic analysis, and information extraction.

CUDA, vLLM, Triton, Ollama, DeepSpeed, FSDP, or related inference technologies.

Fine-tuning experience (SFT, DPO) and dataset curation.

Master's or PhD in Artificial Intelligence, Machine Learning, Computer Science, or a related field.

Who You'll Be

A systems thinker who understands how infrastructure, models, and products work together.

A hands-on builder who enjoys shipping production-ready solutions.

An adaptable professional who thrives in a fast-moving startup environment.

A leader who can elevate the performance of a growing AI team.

If you're passionate about building cutting-edge AI systems and want to help shape the future of intelligent products, we'd love to hear from you.

To apply, please email your resume to: [usman.z@wigiwork.com](mailto:usman.z@wigiwork.com) or DM

Hi everyone,

I'm Sankaranathan D, a B.Tech AI & Data Science student (2023-2027) from Chennai, looking for full-time AI Engineer / Multi-Agent Systems roles.

**Key Skills:**

- AI Agent Harness Engineering, Multi-Agent Orchestration

- Context Engineering, Automation, System Design

- Python, ML Pipelines, OpenCode Custom Agent Development

**Featured Project — Supernova:**

Multi-agent orchestration system with 100+ subagents, 7 MCPs, and 48 skills. Open-source project demonstrating advanced agent coordination and context management.

**Looking for roles involving:**

- AI Agent Systems design

- Multi-agent orchestration platforms

- Python backend development

- ML pipeline construction

- Automation workflows

Open to full-time, internship, or contract roles . Happy to discuss how my agent engineering experience can contribute to your team!

We’re looking for experienced professionals to conduct hands-on AI training sessions on weekends.

What you’ll do:

- Conduct live, 3-hour sessions on Saturdays and Sundays.

- Teach practical AI applications, tools, and workflows through demos and exercises.

- Develop session content and keep it updated.

Requirements:

- 6–8 years of experience in the software/IT industry.

- Strong practical knowledge of AI tools, applications, or AI engineering.

- Good communication skills and the ability to explain concepts through real-world examples.

- Prior training experience is a plus, but not mandatory.

Commitment: Weekends, approximately 8–12 hours/week.

Compensation: ₹2,500–₹3,500/hour, depending on experience and topic.

Interested? DM me with your experience and areas of expertise.

Can't sleep, can't switch off, or tired of YouTube yoga that doesn't know you exist? I teach live 1:1

- Yoga nidra and deep relaxation: for sleep, stress and burnout
- Personal yoga sessions: built around your body, level and goals

10 years of teaching, based in Uttarakhand, India. Evening or early-morning slots to fit US, UK and Europe time zones.

DM me what you're struggling with and I'll suggest where to start.

What's the one thing keeping you from a regular practice?

Hi everyone!

I'm a final-year Engineering student at SUP'COM (Tunisia), specializing in Artificial Intelligence and Data Science, currently looking for a 5–6 month end-of-studies internship (PFE) starting in February/March 2027, preferably in Europe.

I have hands-on experience developing AI solutions through internships, R&D projects, and production-oriented systems.

A quick overview of my background:

• Computer Vision & Deep Learning: Developed medical image classification models using ConvNeXt/Swin Transformers, achieving 93% validation accuracy. Also worked on real-time object detection and tracking with YOLO/ByteTrack.
• LLMs, VLMs & AI Agents: Experience building document-understanding pipelines, structured data extraction systems, and AI agents using LangGraph, FastAPI, MCP, and PostgreSQL.
• 3D Perception & Robotics: Built real-time LiDAR perception pipelines using ROS2, C++, PCL, PointPillars, and CUDA, with experience in 3D detection and tracking.
• Multimodal AI & Image Processing: Developed ClearSky-4D, a multimodal satellite image restoration project combining Sentinel-1 SAR and Sentinel-2 optical imagery using U-Net architectures.

Tech stack: Python, PyTorch, TensorFlow, C++, CUDA, OpenCV, ROS2, Docker, Git, FastAPI, and related ML tools.

I'm particularly interested in opportunities involving Computer Vision, Multimodal/Generative AI, AI Agents, Robotics, or Applied Machine Learning, especially projects involving research, experimentation, and real-world deployment.

I'm motivated by challenging technical problems, enjoy learning from experienced engineers and researchers, and would love to contribute to an innovative team.

If your team is hiring interns, or you know someone looking for a motivated AI/ML engineering intern, I'd really appreciate a connection or referral!

Feel free to DM me. I'd be happy to share my resume, GitHub, projects, and further details.

Thanks for reading!

I'm a B.Tech student specializing in Computer Science (AI & ML), currently looking for internship opportunities to gain practical experience and work on real-world projects.

I've been working on AI/ML projects, including a digital twin and predictive maintenance concepts, and have experience with Python, NumPy, Pandas, Scikit-learn, and machine learning model training and evaluation.

I'm open to beginner-friendly roles and willing to learn new tools and technologies as required.

I'd really appreciate any guidance. Thanks!

Hi ,

I'm a final year student looking for an internship in applied ML and computer vision roles. Anyone hiring or knowing any referrals, Dm me and that helps me a lot. I have also worked on research papers and a few published ones.

About Modular

At Modular, a Qualcomm company, we’re on a mission to revolutionize AI infrastructure by systematically rebuilding the AI software stack from the ground up. Our team, made up of industry leaders and experts, is building cutting‑edge, modular infrastructure that simplifies AI development and deployment. By rethinking the complexities of AI systems, we’re empowering everyone to unlock AI’s full potential and tackle some of the world’s most pressing challenges.

If you’re passionate about shaping the future of AI and creating tools that make a real difference in people’s lives, we want you on our team.

About the role:

MAX is Modular's inference tech stack, built to run GenAI models fast across NVIDIA, AMD, Qualcomm, Trainium, TPU and more. The MAX Kernel team is the performance foundation of that stack, developing kernels using Mojo, GEMM, attention (MHA/MLA/MSA), MoE routing and grouped matmul, and the portable tile abstractions that let one kernel lower to many targets.

As the Engineering Manager of the MAX Kernel team, you will lead a team of kernel engineers, own the kernel roadmap and the per-model × per-hardware performance optimization to the best vendor and open-source stacks. You will partner closely with the Framework, Serve, Compiler/Runtime and Hardware Enablement teams, and help grow a kernel engineering community that spans Modular and Qualcomm.

LOCATION: Candidates based in the United States are welcome to apply. You can work in our office in Los Altos, CA or remotely from home. Onboarding for new hires is conducted in‑person in our Los Altos, CA office.

What you will do:

• Lead, hire, coach and grow a team of ~12 kernel engineers across NVIDIA, AMD and ASIC hardwares; own career development, performance management and team health.
• Own the MAX kernel roadmap and delivery: match or beat the performance of other open‑source kernel libraries on each business essential model × hardware target.
• Support portable kernel architecture (TileTensor / TensorEngine / TileIO, reusable building blocks such as MegaFFN and the attention family) together with tech leads.
• Partner cross‑functionally with Framework, Serve, Compiler/Runtime, Hardware Enablement and Qualcomm kernel teams on priorities, interfaces and escalations.
• Advance AI‑assisted kernel development (kernel agents, fuzz verification, playbooks) and the kernel engineering community across org boundaries.

What you bring to the table:

• 3+ years as an engineering manager leading GPU kernel, compiler, HPC, or ML performance engineering teams. minimum requirement
• Strong cross‑functional communication; able to drive technical decisions with tech leads and communicate status, risks and tradeoffs to engineering leadership and customers.
• Track record of hiring, retaining and growing senior kernel or performance engineers.
• Working knowledge of writing and optimizing GPU/accelerator kernels (CUDA, HIP/ROCm, Triton, CUTLASS/CuTe or similar).
• Deep understanding of profiling, benchmarking, and roofline analysis

Helpful, but not required:

• Experience with Mojo or other kernel and tile‑level programming models (Triton, TileLang, CuTe)
• Multi‑target experience beyond NVIDIA: AMD, NPUs/ASICs or edge/on‑device.
• Experience with AI‑assisted or agentic kernel development.
• Open‑source contributions to kernel libraries or inference engines.

What Modular brings to the table:

• Amazing Team. We are a progressive and agile team with some of the industry’s best engineering and product leaders.

• World‑class Benefits. In order to attract the best, we need to offer the best. Your benefits package may include comprehensive healthcare coverage, retirement and savings programs, employee stock purchase opportunities, paid time off, wellbeing resources, family support programs, and learning and development opportunities. *Please note that specific benefit packages may vary based on your location.

• Competitive Compensation. We offer very strong compensation packages, including RSU grants. We want people to be focused on their best work and believe in tailoring compensation plans to meet the needs of our workforce.

• Team Building Events. We organize regular team onsites and local meetups in Los Altos, CA as well as different cities. Traveling 2‑4 times a year is expected for all roles.

Working at Modular will enable you to grow quickly as you work alongside incredibly motivated and talented people who have high standards, possess a growth mindset, and a purpose to truly change the world.

The estimated base salary range for this role to be performed in the US is $255,400.00 - $383,200.00 USD.

The salary for the successful applicant will depend on a variety of permissible, non‑discriminatory job‑related factors, which include but are not limited to education, training, work experience, business needs, or market demands. This range may be modified in the future. The total compensation for a candidate will also include annual target bonus, equity, and benefits, with equity making up a significant portion of your total compensation.

For candidates who fall outside of the listed requirements, we nevertheless encourage you to apply as we may have upcoming openings that are lower/higher level than the ones advertised.

Location: United States - Remote

Remote: Yes

Department: MAX

Office: United States

Employment Type: Full-time

Apply: AI Kernel Engineering Manager at Modular Inc

Hi,

I am a graduate from IIT Kharagpur.

I am looking for job opportunities as an AI engineer role in Netherlands. Currently I am based in India.

I have around 5 years of experience building AI systems, Agentic workflows, Fine tuning LLMs and managing LLM infrastructures.

Please find my portfolio:

Website: https://www.neatcraft.ai/

GitHub: https://github.com/mukeshbarnwal

Please let me know if there are any leads.

Regards.

Hi all, I'm Ram, a 2026 computer science graduate from India looking for my first full-time AI/ML engineer role. Remote works great for me, and I'm open to relocating.

The project I'm proudest of is ARGUS, a multi-agent AI platform for auditing smart contracts. It's the clearest example of how I like to work: take a messy, high-stakes problem, break it into steps that can be checked, and ship something people can use.

I also do smart contract security. I've done 7 private audits, including a Critical bug in a Solana lending protocol. I'm certified from the RektOff x Solana Foundation Rust Security Bootcamp, wrote Anchor-Sentinel (a Rust static analyzer for Anchor programs with 20+ detectors), and had a PR merged into DeFiLlama.

Looking for: junior AI/ML or applied LLM engineer roles, ideally on a team building agents or evaluation tooling. Open to freelance work too.

Portfolio: ramprasadgoud.dev Code: github.com/Ramprasad4121 Quick call: calendly.com/ramprasadedigi/30min

Reddit DMs are open. Thanks for reading.

For a research project in the cultural sphere, we’re looking for someone to help us scrape unstructured data from across the web, clean it, integrate it with our own data sources, and ultimately connect everything into one reliable dataset. On top of that dataset, you’ll build a multimodal embedding space to uncover relationships and patterns within the data.

Experience with web scraping, data pipelines, data engineering and multimodal embeddings is essential, and you should be comfortable working with agentic coding tools. We’re not looking for any specific academic background, but for someone savvy, resourceful and quick who has done this kind of work before.

DM me with a little bit about you. :)

[Hiring] AI/ML Engineer — hands-on building with real technical ownership

We’re looking for an AI/ML engineer who wants to help shape a product, make technical decisions, and own what they build—not just work through assigned tickets.

The work involves AI systems for complex, document-heavy professional workflows. More details about the product will be shared privately.

You’ll work closely with a small team, taking problems from user requirements through architecture, implementation, evaluation, deployment, and ongoing improvement. We’re looking for someone who can challenge an approach, propose a better one, and follow through on execution.

What you’ll work on

- Document intelligence and retrieval: document-processing pipelines, RAG, embeddings, reranking, and source-grounded responses.

- Agents and model integration: multi-step workflows, tool use, open-source and hosted models, and integration with the application.

- Production reliability: evaluations, debugging, monitoring, failure handling, and improving accuracy, latency, and cost.

What we’re looking for

Strong Python skills, practical experience with LLM-based systems, and enough backend and deployment knowledge to take a feature into production. Experience with fine-tuning, document understanding, or agent orchestration would be useful, but you don’t need to have worked with every framework.

Your actual work matters more than a list of tools on your résumé. We’d like to understand what you personally built, why you made particular decisions, what failed, and how you fixed it.

Ownership here means having meaningful input into the technical direction and being responsible for how your systems perform after deployment. It also means communicating clearly, recognising when something needs more investigation, and asking for help rather than hiding uncertainty.

DM with your location, availability, and GitHub, résumé, or relevant project links. Include a brief example of an AI system you worked on: what you personally owned, the hardest problem you encountered, and how you addressed it.

Hello I'm 28 ML/AI Engineer worked in two companies in my carrier and developed several projects related to time series forecasting i left my last company because the project contains alcoholic products sine the end of January i been having interviews with several companies but none of them sent me a real offer ,also i studied AI Engineering industry by reading

Hands on LLms by Jay Alammar book

AI Engineering by chip huyuen book

Core Track (LLM Engineering) course by ED Donner

With several books not finished yet

Also i got opportunity to work in industries like banking/Media but it can't work at that sectors

[Hiring] Remote · Contract · $80–$140/hr

Company: micro1 (https://www.micro1.ai) — data lab helping AI labs and enterprises train foundational models and agents.

Role: Machine Learning Engineer as a remote AI-training expert contractor. You use ML judgment to review outputs, evaluate quality, and give structured feedback that improves model behavior. Not a clinic or product-eng job. Project-based.

Requirements: solid ML background. Prior AI-training gigs optional.

How to apply: https://jobs.micro1.ai/post/3751d160-6ea1-45e9-8c40-7af439059844?referralCode=dbc0ccb6-7b9d-4905-abd1-3e7d0072c065

Apply through the link. micro1 handles screening. Please don’t spam DMs.

Disclosure: I’m not micro1 staff or a recruiter — this is my personal micro1 referral link and I may get a referral bonus if you’re placed.

Hi, I have to Prepare for OA and Interview rounds for Tiger Analytics. I love to hear from you if you have experience with the interview process.

Thanks in advance.

I’m a 2026 Computer Science graduate specializing in Generative AI, AI Automation, LangChain, and RAG systems.

I build and work with:

• AI Automation — turning repetitive business workflows into intelligent automated systems
• LangChain — LLM applications, tool integration, agents and data connections
• RAG — connecting LLMs with private/company data to build useful, context-aware systems
• AI Agents & LLM integrations
• Prompt Engineering
• Python & AI/ML solutions
• Business-focused AI implementations

I’m particularly interested in working with startups where AI isn't just a buzzword — it's being used to build products, automate operations, improve efficiency, or create something genuinely new.

I’ve chosen to bet on my capabilities and build my career around where I believe the future is going — AI, automation and intelligent systems.

So, if you're a founder building something ambitious and need someone who can think beyond prompts and actually work on AI systems, automation and integrations, let's talk.

If your startup has a problem that can be solved with AI, I want to hear about it.

DM me. 🚀

A candidate has a technical interview in a few days for an MLE internship on TikTok's data search/visual search team. How would you divide the remaining prep time?

The immediate question is how much to spend on coding versus ML fundamentals and search/computer vision concepts. Intern-level advice would be especially useful: which ideas should a candidate be able to explain clearly, and what kinds of practice helped connect the theory to an actual interview discussion?

TikTok Interview Questions can help organize company-specific practice, though the team and role still matter when choosing prompts. If other internship applications are eating into the remaining days, application autofill and Agent autoapply can reduce the repetitive admin.

If you've interviewed with this team or a similar one, what was worth reviewing? What would you leave out when time is this short?

Disclosure: I operate PracHub and LandOffer.