Junior AI/ML Engineer

Build the Next Generation of AI Products with TensorOps

TensorOps is an applied machine learning and artificial intelligence studio helping organizations worldwide plan, design, train, and deploy production-grade ML systems. Our clients range from NASDAQ-listed enterprises to seed-stage startups. Projects span from small proofs-of-concept to multi-year strategic initiatives.

What We’re Working On

• Generative AI applications: Chatbots and Agents
• Traditional Machine Learning: Time Series Forecasting, AdTech, Computer Vision, etc.
• MLOps: Improving ML pipelines at scale

Core Stack

As we work with many clients, our stack varies, but we often use:

• Python APIs: FastAPI
• Containerization: Docker, Kubernetes
• Model Training & Serving: LightGBM, CatBoost, PyTorch, HuggingFace
• Data Engineering: Pandas, Polars
• LLM Frameworks: LangChain, LangGraph
• Observability: MLFlow, Langfuse
• Cloud Platforms: AWS, GCP
• Search: Elasticsearch, OpenSearch, Solr

The Role

We’re looking for a Junior Machine Learning Engineer to help us deliver projects rapidly. You’ll report to and be mentored by a senior team member. This is a hands-on role from day one, working on real projects that make a tangible impact.

Preferred Qualifications

• BSc in Computer Science, Software Engineering or equivalent
• MSc in Computer Science, Data Science, AI or equivalent

Required Skills

• Solid software engineering fundamentals (OOP, Git, concurrency, parallelism)
• Proficiency in Python
• Understanding of LLM system design (RAG, agents, etc.)
• Knowledge of ML system design (pipelines, training/inference techniques)
• Excellent English communication skills

Nice to Have

• Experience in non-academic projects (jobs, internships or similar)
• Previous LLM projects (academic or professional)