Senior Machine Learning Engineer (Computer Vision)

Quick Facts

• Role: Senior Machine Learning Engineer (Computer Vision)

• Focus: Production-grade computer vision solutions and end-to-end ML delivery

Description

Lead the design, development, and deployment of reliable, maintainable, and scalable computer vision models in production. Drive ML projects from problem definition through deployment and long-term maintenance, turning business/product requirements into scalable architectures. Build reusable Python ML infrastructure and tooling, and continuously improve model quality via experimentation and data-driven iteration.

Responsibilities

• Own complex ML projects across the full ML lifecycle (data strategy, annotation, datasets, experimentation, development, deployment, monitoring, and continuous improvement)

• Design and deploy production-ready computer vision solutions

• Translate business and product requirements into scalable ML architectures

• Develop reusable Python libraries, ML frameworks, and internal tooling

• Improve model quality with rigorous experimentation, performance analysis, and data-driven decisions

• Lead engineering initiatives for reproducibility, testing, CI/CD, observability, MLOps, and deployment best practices

• Mentor ML engineers through technical guidance and code reviews

• Contribute to technical architecture decisions for the long-term ML platform

Requirements

• 5+ years of commercial experience building and deploying machine learning systems

• Strong ML fundamentals (supervised, unsupervised, self-supervised; optimization; probability/statistics; linear algebra; evaluation/validation)

• Deep understanding of operating ML systems in production

• Excellent Python engineering skills (clean, maintainable, testable code; algorithms/data structures; debugging/performance optimization; reusable libraries/APIs)

• Extensive experience with deep learning models using PyTorch

• Production ML systems experience with scalability, reliability, maintainability

• Proven ability to balance data quality, evaluation, software engineering, and deployment

• Ability to independently lead technical initiatives from concept to production

• Experience mentoring and technical leadership

• Strong communication skills for technical and non-technical stakeholders

Benefits

• Direct collaboration with founders and meaningful technical ownership

• Chance to shape the AI platform direction and tackle real customer problems

• Career growth in a fast-paced startup environment

• Hybrid work model

• Fitness and health membership benefits

• Gaming laptop for work

• Company off-sites and team activities