Senior Machine Learning Engineer, Computer Vision at Metropolis

Los Angeles, California, United States

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Not SpecifiedCompensation

Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

Artificial Intelligence, TechnologyIndustries

Requirements

MS or PhD (preferred) 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). Experience with C++ is a plus
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 in high-growth, innovative environments is a plus
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

Skills

Key technologies and capabilities for this role

Computer VisionObject DetectionObject TrackingOCRDeep LearningMulti-modal ModelsModel DeploymentData PipelinesVideo AnalyticsGPU OptimizationEdge Computing

Questions & Answers

Common questions about this position

What qualifications and experience are required for this Senior Machine Learning Engineer role?

Candidates need an MS or PhD (preferred) in Computer Science, Engineering, or a related field, or equivalent experience, plus 5+ years of hands-on experience in machine learning and computer vision with a track record of deploying models to production.

What technical skills and tools are essential for this position?

Proficiency in Python and ML frameworks like PyTorch/TensorFlow/ONNX/TensorRT is required, with C++ as a plus. Strong experience in model optimization (e.g., quantization, pruning) and deployment on cloud, edge, or mobile platforms is also needed, along with familiarity with AWS, GCP, Azure, Docker, and ECS/Kub.

Is this a remote position, or does it require office work?

This information is not specified in the job description.

What is the salary or compensation for this role?

This information is not specified in the job description.

What does a strong candidate for this role look like?

A strong candidate has an advanced degree or equivalent, 5+ years deploying ML/CV models in production, expertise in Python and frameworks like PyTorch/TensorFlow, model optimization skills, and experience with cloud platforms and containerization, plus the ability to mentor juniors.

Metropolis

Technology-driven facility management for parking

About Metropolis

Metropolis focuses on improving facility management, particularly in the parking sector, by using computer vision technology to facilitate checkout-free payments. This technology allows drivers to park and pay without the need for traditional payment methods, making the process more efficient. Metropolis serves a variety of clients, including real estate owners and valet services, and operates in over 360 cities across North America, processing more than $4 billion in payments each year. What sets Metropolis apart from its competitors is its integration of payment solutions with facility management services, which not only enhances the parking experience but also increases asset productivity for its clients. The company's goal is to streamline parking operations and create revenue opportunities for its clients through its advanced technology and services.

Santa Monica, CaliforniaHeadquarters

2017Year Founded

$1,240.7MTotal Funding

DEBTCompany Stage

Automotive & Transportation, Fintech, Real EstateIndustries

501-1,000Employees

Benefits

Health Insurance

401(k) Retirement Plan

Disability Insurance

Life Insurance

Stock Options

Performance Bonus

Risks

Increased competition from BMW-owned ParkMobile may impact market share.

The SP Plus acquisition may pose integration challenges and financial strain.

Rapid expansion could lead to operational inefficiencies and quality control issues.

Differentiation

Metropolis uses AI and computer vision for checkout-free parking payments.

The company integrates its platform into field operations for revenue generation.

Metropolis serves diverse clients, including real estate and valet services.

Upsides

Metropolis processes over $4 billion in payments annually across 360 cities.

The acquisition of SP Plus Corporation expands Metropolis's market reach.

AI-driven dynamic pricing models optimize revenue in real-time.

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