Machine Learning Engineer
New
S
SurveilyAI, Computer Vision
Wrocław, Country code: PLContractMiddle
Salary15000 - 22000 PLN per month b2b
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Job Details
- Languages
- Pl B2, en B2
- Experience
- 3-5 years of commercial experience
- Required Skills
- DockerPythonGitMachine LearningPyTorchDeep LearningComputer Vision
Requirements
- 3-5 years of commercial experience building machine learning systems.
- Strong understanding of machine learning fundamentals (supervised, unsupervised, and self-supervised learning, optimization, probability and statistics, linear algebra, model evaluation and validation).
- Solid understanding of the complete machine learning lifecycle and production challenges.
- Strong Python software engineering skills (clean, maintainable, testable code, algorithms, data structures, debugging, performance optimization, designing reusable libraries).
- Experience developing deep learning models using PyTorch.
- Ability to independently own technical problems from definition through production delivery.
- Strong communication skills and ability to translate business problems into technical solutions.
- B2 proficiency in Polish (pl).
- B2 proficiency in English (en).
Responsibilities
- Design and deliver production-ready computer vision features from concept to deployment.
- Translate product and business requirements into practical machine learning solutions.
- Work across the complete ML lifecycle, including data collection, annotation strategy, dataset management, experimentation, model development, evaluation, deployment, monitoring, and iteration.
- Build robust Python tooling and shared libraries that improve the productivity of the ML team.
- Develop reliable, maintainable, and well-tested production code.
- Collaborate closely with software engineers and product stakeholders to deliver measurable customer value.
- Continuously improve model quality using data-driven experimentation rather than research for its own sake.
- Help establish engineering best practices around reproducibility, testing, documentation, and MLOps.
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