Senior Machine Learning Engineer, Computer Vision

About the role

The real world is the next frontier, and at Metropolis, we are creating the artificial intelligence to make it responsive. We are pioneering the Recognition Economy — a future where mundane repetition disappears and being known unlocks access, comfort and belonging everywhere you go. From transforming parking into a seamless drive-in, drive-out experience for millions of Members to expanding our intelligence layer across retail and hospitality, we are building a world that feels instinctive and magical. The future isn’t coming; it’s here, and we need builders, innovators and problem solvers to help us create it.

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

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
• Experience leveraging AI tools to transform static workflows into responsive, high-output processes

Qualifications

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

Skills

• Advanced knowledge of computer vision and machine learning
• Experience with deep learning frameworks and tools
• Strong problem-solving and analytical skills
• Ability to work effectively in a fast-paced, dynamic environment
• Excellent communication and collaboration skills

Benefits

Metropolis offers a competitive benefits package, including:

• Healthcare benefits
• A 401(k) plan
• Short-term and long-term disability coverage
• Basic life insurance
• A lucrative stock option plan
• Bonus plans

Pay

The anticipated base salary for this position is $150,000.00 to $200,000.00 annually. The actual base salary offered is determined by a number of variables, including, as appropriate, the applicant's qualifications for the position, years of relevant experience, distinctive skills, level of education attained, certifications or other professional licenses held, and the location of residence and/or place of employment.

Schedule

Metropolis values in-person collaboration to drive innovation, strengthen culture, and enhance the Member experience. Our corporate team members hold to our office-first model, which requires employees to be on-site at least four days a week, fostering organic interactions that spark creativity and connection.