Machine Learning Engineer - Computer Vision

About this role

<div class="content-intro"><h2>Hi, we’re CompanyCam.</h2> <p>We’re a simple-to-use photo documentation and productivity app for contractors of all commercial and home services industries. Packed with intuitive functionality, CompanyCam facilitates unparalleled communication and accountability across a contractor’s entire business. We’re committed to providing a consumer-grade, game-changing experience that helps our users build trust within their company and with their customers.</p> <p>But don’t let that corporate description fool you—the people behind our buttoned-up product are laid-back (but hardworking), genuine, and kickass, and you could be one of them!</p></div><h2>The Role</h2> <p>We're looking for a <strong>Machine Learning Engineer</strong> with deep computer vision experience to join our ML team.</p> <p>Contractors capture millions of jobsite photos through CompanyCam every day. As an ML Engineer, you'll turn that visual data into structured understanding — building and shipping computer vision systems that power image classification, document detection, segmentation, multimodal embeddings, and more across 70,000+ projects daily.</p> <p>This is a small team with outsized reach. You'll own problems end-to-end, from data preprocessing and model training through evaluation and production deployment. You won't be tuning hyperparameters on someone else's model — you'll make architectural decisions and see your work in the hands of real contractors on real jobsites.</p> <p>Current and near-term problems include segmentation, on-device model deployment, vision-language model integration, and building the evaluation infrastructure to do it all sustainably.</p> <h2>Working At CompanyCam</h2> <p>Our engineering team is remote-first, spanning every time zone in the United States. We welcome people from all backgrounds and really don't care whether or not you have a CS degree or even a high school diploma. All that matters is that you're not a jerk and you're good at what you do.</p> <p>At CompanyCam we're driven to produce work with meaningful outcomes. That means not just dumping features and "improvements" but being able to reflect and learn from our outputs.</p> <h2>What You'll Do</h2> <ul> <li>Design, train, and deploy computer vision models to production with well-understood performance, latency, and cost characteristics.</li> <li>Own the full ML pipeline: data preprocessing, feature engineering, model selection, training, evaluation, and deployment into sustainable inference services.</li> <li>Conduct discovery spikes to validate feasibility and inform go/no-go decisions before committing to full development.</li> <li>Integrate ML solutions with observability tooling, establishing and maintaining benchmarks to measure improvement and compare approaches.</li> <li>Build automated, self-sustaining ML pipelines. Models should train, evaluate, and deploy with minimal manual intervention.</li> <li>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.</li> <li>Collaborate with software engineers, data engineers, and product stakeholders to integrate ML solutions into CompanyCam's platform.</li> <li>Communicate clearly with non-technical audiences about feasibility, requirements, and trade-offs of proposed solutions.</li> </ul> <h2>What You'll Bring</h2> <h3>Must-haves</h3> <p>These are our non-negotiables:</p> <ul> <li><strong>Show up:</strong> give us your best and have the courage to do difficult but necessary stuff.</li> <li><strong>Grow up:</strong> be humble, take responsibility, learn continuously, and have a growth mindset.</li> <li><strong>Do good:</strong> treat your co-workers and customers the way you want to be treated.</li> <li>3+ years of experience shipping machine learning models to production (not just training them).</li> <li>Experience with computer vision techniques including image classification, segmentation, and object detection.</li> <li>Strong coding skills in Python with proficiency in PyTorch or TensorFlow and comfort with modern architectures (transformers, CNNs, etc.).</li> <li>Strong SQL skills including joins, subqueries, window functions, and CTEs.</li> <li>Proficiency in data analysis, cleaning, transformation, and feature engineering.</li> <li>Experience with version control (Git), experiment tracking, and ML development best practices.</li> <li>Ability to explain technical concepts to non-technical stakeholders through clear writing and presentations.</li> <li>You live and work permanently in the U.S. (We're not set up to hire outside the U.S.).</li> </ul> <h3>Nice-to-haves</h3> <p>You'll encounter the following with varying frequency. Experience with them is a plus, but not required:</p> <ul> <li>Embeddings, vector databases, and similarity search</li> <li>On-device model deployment (e.g., Core ML, TensorFlow Lite)</li> <li>MLFlow, Weights & Biases, or similar experiment tracking platforms</li> <li>Amazon Bedrock or other cloud ML services</li> <li>Ruby on Rails or JavaScript/React (for integration work)</li> </ul> <h2><strong>Benefits and Compensation</strong></h2> <p>This is a salaried position at CompanyCam. Our salary range…