Machine Learning Engineer – Computer Vision

🕒 April 27

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CompanyCam

51 - 200 employees

Founded 2015

☁️ SaaS

🏗️ Construction

💰 $30M Series B on 2021-10

SaaS • Construction

CompanyCam is a software platform designed specifically for contractors to manage their job site documentation. It provides tools for photo and video capture, annotations, in-app communications, and collaborative features that allow teams to document and track job progress in real-time. The platform supports integrations with other software and offers AI-powered actions to generate reports and organize information. CompanyCam is widely used across various trades, helping professionals keep projects organized, maintain accountability, and effectively communicate with teams and clients.

📋 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

• meaningful equity • and other benefits

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