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TensorOps

Junior Machine Learning Engineer

TensorOps
Portugal · Full-time · Not Applicable

Build the Next Generation of AI Products with TensorOps

TensorOps is an applied machine learning 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

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.

Required 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

Key Skills

Ranked by relevance

ai machine learning computer vision pytorch docker pandas mlflow cloud git aws oop
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Posted
Aug 04, 2025
Type
Full-time
Level
Not Applicable
Location
Portugal
Company
TensorOps

Industries

Software Development

Categories

Engineering

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