Senior Machine Learning Engineer, Computer Vision

Metropolis•Seattle, WA

1d•$150,000 - $200,000•Hybrid

About The Position

We are seeking a Senior Machine Learning Engineer to play a key role to join our growing team. As a key member of the Advanced Technologies team, you will play a critical role in designing, developing, and deploying state-of-the-art computer vision and recommendation models that power our core products and solutions. Your work will involve tackling challenging problems in object detection, tracking, OCR, video analytics, and multi-modal systems. This role involves a unique blend of technical expertise in data and machine learning, innovative thinking, and a passion for data-driven solutions.

Requirements

PhD in Computer Science, Engineering, or a related field, or equivalent work experience
5+ years of hands-on experience in machine learning and computer vision, with a strong track record of deploying models into production
Proficiency in Python and ML frameworks (PyTorch/TensorFlow/ONNX/TensorRT)
Strong experience with model optimization (e.g., quantization, pruning) and deployment on various platforms (cloud, edge, or mobile)
Familiarity with cloud platforms (AWS, GCP, or Azure), containerization (Docker), and orchestration (ECS, Kubernetes)
Proven experience in building and maintaining data pipelines (e.g., Airflow)
Strong understanding of the agile development process and CI/CD pipelines and tools (e.g., Github Actions, Jenkins)
Excellent communication skills, capable of presenting complex technical information clearly

Nice To Haves

Experience with C++
Experience in high-growth, innovative environments
Publications in top-tier conferences (e.g., CVPR, ICCV, NeurIPS) are a strong plus

Responsibilities

Design, develop, and deploy advanced computer vision models for real-world applications, including object detection, tracking, OCR, image search, and scene understanding
Build and optimize deep learning models, ensuring high accuracy, performance, and scalability for deployment in production environments
Explore and integrate multi-modal approaches, leveraging visual, textual, and other data modalities for robust solutions
Collaborate with cross-functional teams, including data engineers and software engineers to deliver end-to-end solutions
Lead the design and implementation of scalable pipelines for data processing, model training, and model deployment
Optimize models for performance on various hardware platforms, including CPUs, GPUs, and edge devices
Conduct thorough experimentation and A/B testing to validate model effectiveness and ensure alignment with business objectives
Mentor junior team members, providing technical guidance and fostering professional growth
Write clean, efficient, and maintainable code while adhering to best practices in software engineering and machine learning