Machine Learning Engineer

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 an a**hole and you're good at what you do.

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. We’re actively working to center our work on continuous discovery habits (CDH) as outlined by Teresa Torres.

Okay, that’s how we identify work to do, but how do we actually work? Our teams are made up of a product manager, a product designer, a tech lead and an appropriate number of engineers for the scope of your team. We take a flexible approach, pulling from Agile, Scrum, Kanban, and even Shape Up. Rather than being overly prescriptive, we provide guardrails and just enough constraints to keep teams moving. Each team is expected to collaborate, iterate, and refine their best practices to produce high-quality work.

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 an a**hole and you're good at what you do.

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. We’re actively working to center our work on continuous discovery habits (CDH) as outlined by Teresa Torres.

Okay, that’s how we identify work to do, but how do we actually work? Our teams are made up of a product manager, a product designer, a tech lead and an appropriate number of engineers for the scope of your team. We take a flexible approach, pulling from Agile, Scrum, Kanban, and even Shape Up. Rather than being overly prescriptive, we provide guardrails and just enough constraints to keep teams moving. Each team is expected to collaborate, iterate, and refine their best practices to produce high-quality work.

These are our non-negotiables:

• Show up: Have the courage to do difficult but necessary work
• Grow up: Take ownership, learn continuously, and bring a growth mindset
• Do good: Treat your teammates and customers the way you'd want to be treated
• 1-5 years of experience in machine learning, data science, backend engineering adjacent to machine learning, or a related field
• Strong coding skills in Python and experience with ML libraries (e.g., TensorFlow, PyTorch, Scikit-learn) 
• Proficient in SQL, including joins, subqueries, window functions, and CTEs 
• Skilled in data cleaning, transformation, and feature engineering 
• Strong analytical and problem-solving mindset with a focus on data-driven decisions
• Strong collaboration and communication skills (clearly being able to explain technical concepts to non-technical stakeholders), with openness to feedback and diverse perspectives 
• You live and work permanently in the U.S. (We’re not set up to hire outside the U.S.)

Nice-to-haves:

• Google's Professional Machine Learning Engineer and/or Microsoft's Azure Data Scientist certificate 
• Experience with DE tooling such as DVC, 5tran, Snowflake, etc. 
• Familiarity with Rails, React, and/or React Native, or AWS 

This is a salaried position at CompanyCam. Our salary range is $210,000 - $240,000 per year and is based on experience. We also offer meaningful equity and other benefits.

CompanyCam is an equal-opportunity employer committed to respect, inclusion, and growth. We work hard, take responsibility, and support each other. Great ideas come from all backgrounds, and we carefully consider every applicant without regard to personal characteristics or traits. Even if your work experience doesn’t align perfectly, we encourage you to apply. What really matters to us is your potential, your passion, and your commitment to learning, innovation, and contributing meaningfully to our team.

For any accommodations or technical issues related to the online application or interview process, please email [email protected] and we’ll respond promptly. Please do not include any medical or health information in your message.

Note: Resumes sent to this email will not be reviewed or responded to. To be considered for a position, you must apply directly through our careers page.