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 Mentors