JuniorAI/MLEngineer

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 Mentorshi