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ML Engineer

ISI Emerging Markets Group · Warszawa, MZ, PL

Actively hiring Posted about 1 month ago

Responsibilities

  • Own the full model lifecycle: problem scoping, data exploration, feature engineering, algorithm selection, training, evaluation, and iterative improvement
  • Containerise and serve models via FastAPI based microservices; ensure low latency inference, monitoring, and automated rollback strategies
  • Build reproducible pipelines (training, validation, inference) with CI/CD and infrastructure as code practices
  • Work closely with data engineers, product managers, and domain experts to align ML solutions with business goals
  • Champion clean code, unit/integration testing, code reviews, and documentation for long-term maintainability
  • Stay up to date with the latest ML/AI advancements; prototype and benchmark new techniques (e.g., LLM fine-tuning, vector search, on-device ML). Diagnose and resolve production issues, optimise performance, and continually improve model robustness

Basic qualifications

  • Bachelor’s in CS, Data Science, AI, or equivalent; proven ML/DL production experience.
  • Expert in Python (NumPy, pandas, scikit-learn) and SQL; hands-on with PyTorch or TensorFlow; familiarity with Hugging Face.
  • Prompt engineering, RAG, vector search, and model monitoring; fine-tuning is an advantage; strong feature engineering and classical ML.
  • Docker, AWS (ECS/Fargate, S3, Lambda, SageMaker); CI/CD (Jenkins); MLflow or Metaflow; Prefect or Step Functions; MySQL and DynamoDB.
  • Strong problem-solving skills and data driven decision-making
  • Vigilant about data quality, edge cases, and performance bottlenecks
  • Open, constructive collaboration with cross functional teams; mentorship of junior engineers when required
  • Clear articulation of complex technical concepts to technical and nontechnical stakeholders Very good command of English, written and spoken

Benefits

  • Interesting and fulfilling projects
  • Great working environment in an international company
  • Open and friendly working atmosphere
  • Work-life balance
  • Hybrid working model of 2 days in the office and 3 days from home
  • 4 weeks a year you can work from any location that you choose.

Tags & focus areas

Used for matching and alerts on DevFound
Machine Learning Data Science Pytorch Tensorflow Ai
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