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 otherwise)
• Exposure to AI features in cloud platforms (Sagemaker, Bedrock, Vertex AI)
• Experience working in large codebases

Why TensorOps?

• Fully remote (legal residence in Portugal required)
• Real-world projects, rapid feedback loops, and measurable impact
• Mentorship from engineers who have shipped ML systems at scale
• Competitive compensation and growth opportunities - your growth will be based on ownership and performance rather than periodic reviews (which we still do)

Compensation & Perks:

• Yearly salary: €30,000-35,000
• Travel expenses allowance
• Urban Sports Club membership
• Free Professional Certifications