Machine Learning Engineer

Responsibilities

• Fine-tune and deploy computer vision and deep learning models for object detection, object tracking, and OCR at scale.
• Develop vision-language models and Mixture of Experts architectures, from experimental design through production deployment.
• Arcitect Retrieval-Augmented Generation (RAG) systems, including vector store design, hybrid search strategies, chunking pipelines, and context relevance evaluation.
• Apply MLOps best practices for training, evaluation, deployment, and monitoring of production grade computer vision models, with an emphasis on clean, modular, maintainable code.
• Contribute to our machine learning repositories and optimize models for performance, scalability, and real-time inference across edge and cloud environments.
• Drive performance optimization and scalability of ML systems across edge and cloud environments.
• Collaborate with cross-functional teams to integrate computer vision solutions into end-to-end products, translating research outcomes into measurable platform impact.

Qualifications

• 5+ years of hands-on machine learning experience, with deep specialization in computer vision and a proven track record of shipping models to production.
• Master's degree required (Ph.D. preferred) in Computer Science, Machine Learning, or a closely related field.
• Extensive knowledge of computer vision architectures such as Vision Transformers and VLMs along with OpenCV and PIL.
• Experience with MLOps tools (MLflow, Kubeflow, Docker, Kubernetes) able to own the full model lifecycle from experimentation through production monitoring.
• Experience building and deploying LLM-based systems and Retrieval-Augmented Generation (RAG) pipelines, including vector store integration and retrieval evaluation.
• Strong communicator who can translate complex research findings into actionable decisions for engineering and product stakeholders.

Benefits

• Paid days off (i.e. vacation, sick days, bereavement leave)
• Health and Dental plans
• Retailer plans
• Employee and Family Assistance Program (EFAP)
• Employee referral program