Junior AI/ML Engineer

Description

Summary: TensorOps is seeking a Junior Machine Learning Engineer to contribute to real projects, receiving mentorship to deliver production-grade ML systems. Highlights: 1. Work on real-world AI/ML projects with tangible impact 2. Mentorship from experienced ML system engineers 3. Focus on ownership and performance for career growth **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