Machine Learning Engineer – Computer Vision

Worldwide Salaried Open

Job Description:

Design, train, and deploy computer vision models to production with well-understood performance, latency, and cost characteristics.
Own the full ML pipeline: data preprocessing, feature engineering, model selection, training, evaluation, and deployment into sustainable inference services.
Conduct discovery spikes to validate feasibility and inform go/no-go decisions before committing to full development.
Integrate ML solutions with observability tooling, establishing and maintaining benchmarks to measure improvement and compare approaches.
Build automated, self-sustaining ML pipelines. Models should train, evaluate, and deploy with minimal manual intervention.
Inform build-vs-buy decisions with both technical rigor and business context, understanding when in-house models create competitive advantage vs. when vendor APIs are sufficient.
Collaborate with software engineers, data engineers, and product stakeholders to integrate ML solutions into CompanyCam's platform.
Communicate clearly with non-technical audiences about feasibility, requirements, and trade-offs of proposed solutions.

Requirements:

3+ years of experience shipping machine learning models to production (not just training them)
Experience with computer vision techniques including image classification, segmentation, and object detection
Strong coding skills in Python with proficiency in PyTorch or TensorFlow and comfort with modern architectures (transformers, CNNs, etc.)
Strong SQL skills including joins, subqueries, window functions, and CTEs
Proficiency in data analysis, cleaning, transformation, and feature engineering
Experience with version control (Git), experiment tracking, and ML development best practices
Ability to explain technical concepts to non-technical stakeholders through clear writing and presentations
You live and work permanently in the U.S. (We're not set up to hire outside the U.S.)

Benefits:

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