Mid Machine Learning Engineer · AI / Computer Vision

Surveily is a start-up focused on transforming Health and Safety standards in challenging workplaces worldwide by leveraging Machine Learning and real-time data to ensure safer work environments.

• 3-5 years of commercial experience building machine learning systems.
• Strong understanding of machine learning fundamentals including 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 challenges in production deployment.
• Strong Python software engineering skills including writing clean, maintainable, testable code, algorithms and data structures, debugging, performance optimization, and designing reusable libraries and APIs.
• Experience developing deep learning models using PyTorch.
• Awareness that ML system success depends on data quality, evaluation methodology, deployment, as well as model architecture.
• Ability to own technical problems independently from definition through production.
• Strong communication skills to translate business problems into technical solutions.

Nice to have:

• Experience building production computer vision systems.
• Experience deploying ML models and operating them in production.
• Experience with MLOps tools and practices.
• Experience with Docker, Kubernetes, Triton, or cloud infrastructure.
• Experience improving inference performance and optimizing deployment.
• Experience designing datasets, annotation pipelines, or data quality processes.
• Experience building internal ML frameworks or shared developer tooling.
• Experience shipping customer-facing ML products in a start-up environment.

• 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 ML team productivity.
• 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.
• Help establish engineering best practices in reproducibility, testing, documentation, and MLOps.

Informujemy, że administratorem danych jest Surveily Sp. z o.o. z siedzibą we Wrocławiu, ul. Ślężna 104/2B. Podanie danych obowiązkowych jest niezbędne do realizacji procesu rekrutacji. Zgoda na przetwarzanie danych może zostać wycofana w dowolnym momencie.