Senior ML Engineer - Production Computer Vision (Remote)

Surveily; United States; Remote; USD 180,000 - 240,000; Full time

Benefits offered by this job

Direct founders collaboration

Fully remote work model

Fitness and health membership

Gaming laptop for work

Company off-sites and team activities

Job summary

Surveily is seeking a Senior Machine Learning Engineer to lead production-grade computer vision projects. You will own ML initiatives from problem definition through production deployment and long-term maintenance, building reusable libraries and tooling to accelerate the team.

You will mentor engineers, collaborate with product and software teams, and drive reproducibility, testing, CI/CD, and observability across the ML platform.

Qualifications

• 5+ years of commercial experience in ML engineering and production systems.
• Strong Python software engineering skills and clean, testable code.
• Experience with PyTorch and production ML pipelines.
• Ability to translate business requirements into scalable ML architectures.

Responsibilities

• Lead design, development, and deployment of production-ready computer vision solutions.
• Own complex ML projects from problem definition to production maintenance.
• Translate requirements into scalable ML architectures and data strategies.
• Oversee data annotation, dataset management, experimentation, and monitoring.
• Build reusable libraries, frameworks, and tooling to improve efficiency.
• Deliver reliable, well-tested production code and collaborate with stakeholders.
• Mentor engineers and contribute to ML platform direction.

Skills

Python

PyTorch

ML lifecycle

Distributed systems

Deep learning

Mentoring

Communication

Tools

Docker

Kubernetes

NVIDIA Triton

ONNX

TensorRT

OpenCV

Job description

Surveily is seeking a Senior Machine Learning Engineer to lead production-grade computer vision projects. You will own ML initiatives from problem definition through production deployment and long-term maintenance, building reusable libraries and tooling to accelerate the team.

You will mentor engineers, collaborate with product and software teams, and drive reproducibility, testing, CI/CD, and observability across the ML platform.