Senior Machine Learning Engineer, AI / Computer Vision
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SurveilyComputer vision, workplace safety
Workplace type: remote; Locations: Wrocław, Ślężna 104, Wrocław, Country code: PLContractSenior
Salary20,000 - 30,000 PLN per month
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Job Details
- Languages
- Pl B2, en B2
- Experience
- 5+ years of commercial experience building and deploying machine learning systems.
- Required Skills
- DockerPythonGitKubernetesMachine LearningPyTorchCI/CDDeep LearningMLOpsComputer Vision
Requirements
- Have 5+ years of commercial experience building and deploying machine learning systems.
- Understand supervised, unsupervised, and self-supervised learning, optimization, probability and statistics, linear algebra, and model evaluation and validation.
- Understand the full machine learning lifecycle and the practical challenges of operating ML systems in production.
- Demonstrate strong Python software engineering skills, including clean, maintainable, testable code, algorithms and data structures, debugging, and performance optimization.
- Have experience designing reusable libraries and APIs.
- Have extensive experience developing deep learning models using PyTorch.
- Have experience designing scalable, reliable, and maintainable production ML systems.
- Be able to independently lead technical initiatives from concept to production.
- Have experience mentoring engineers and providing technical leadership.
- Communicate complex technical concepts to technical and non-technical stakeholders.
Responsibilities
- Lead the design, development, and deployment of production-ready computer vision solutions.
- Own ML projects from problem definition through production deployment and long-term maintenance.
- Translate business and product requirements into scalable machine learning architectures.
- Drive data strategy, annotation, dataset management, experimentation, model development, deployment, monitoring, and continuous improvement.
- Design and build reusable Python libraries, ML frameworks, and internal tooling.
- Deliver reliable, maintainable, well-tested, and scalable production code.
- Collaborate with software engineers, product managers, and business stakeholders.
- Improve model quality through experimentation, performance analysis, and data-driven decision making.
- Lead engineering initiatives around reproducibility, testing, CI/CD, observability, MLOps, and deployment practices.
- Mentor Machine Learning Engineers and contribute to technical architecture decisions.
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