Senior Machine Learning Engineer

Full Time

No Sponsorship Provided

Machine Learning Scientist – Computer Vision (Applied AI)

The Role

We are seeking a Machine Learning Scientist to help build and scale production-level AI capabilities for a cutting-edge platform at the intersection of computer vision and real-world applications. This role focuses on designing and deploying algorithms that augment and automate complex decision-making processes using advanced machine learning techniques.

This is a highly applied, high-ownership role, not a pure research position. You will own work end-to-end, from early-stage concept development through deployment in production environments. The ideal candidate has experience translating research into scalable solutions and thrives working cross-functionally with technical and domain experts.

Responsibilities

• Own the full model lifecycle, including dataset generation, annotation, model design, training, evaluation, deployment, and monitoring
• Partner with cross-functional teams to design and execute large-scale experiments that bring new capabilities into production
• Develop and maintain production-quality code, and actively participate in code reviews
• Stay current with advancements in machine learning and computer vision, and apply relevant innovations to real-world problems
• Create clear technical documentation and communicate progress and results to both technical and non-technical stakeholders

Requirements

• Strong foundation in machine learning and computer vision through advanced degree (MS/PhD) and/or industry experience
• Proven experience building, deploying, and maintaining AI/ML systems in production environments
• 5\+ years of hands-on experience in machine learning, with a preference for industry experience
• Deep expertise in image processing, particularly with large-scale, high-dimensional image data
• Experience working with ML and computer vision frameworks such as PyTorch, TensorFlow, scikit-learn, or OpenCV
• Strong Python skills and solid software engineering practices
• Experience designing and executing rigorous experiments and interpreting results effectively
• Ability to communicate clearly across technical and non-technical audiences

Preferred Qualifications

• Experience working with biological, biomedical, or microscopy image data
• Familiarity with image segmentation, object detection, or morphology analysis
• Background in life sciences, biophysics, or a related field
• Experience with modern approaches such as self-supervised learning, contrastive learning, or foundation models
• Exposure to reinforcement learning or sequential decision-making
• Experience with cloud platforms such as AWS or GCP