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

- Travel expenses allowance

- Urban Sports Club membership

- Free Professional Certifications