Machine Learning Engineer

Building hardware is like writing software with no debugger, no logs, and only three compile attempts—before mass production. This lack of visibility leads to costly waste.
Instrumental’s AI-powered platform gives hardware teams the data and insights they need to catch and fix issues early. Leading brands like Meta, Bose, and Cisco use it to build better products, faster, with less waste.
We’re a ~70-person, mission-driven team that values inclusivity and impact. If that resonates with you, let’s talk.
About The RoleWe’re looking for a customer-focused ML Engineer to help build and scale our end-to-end ML pipeline. You’ll balance research and productization in a fast-paced, collaborative environment.
At Instrumental, ML engineers don’t just develop models—they drive real impact. You’ll own the full lifecycle of machine learning projects: from shaping features alongside product to exploring cutting-edge research, building and refining datasets, running rapid experiments, deploying at scale, and monitoring live performance. You’ll work in a deeply collaborative environment where your ideas directly shape the product and deliver measurable value to world-class hardware teams. If you’re looking for meaningful ownership, real-world impact, and the chance to work on high-leverage problems with a smart, mission-driven team—this is the place.

What You'll Do

• Own ML pipelines end-to-end—from prototyping to deployment to measuring customer impact
• Focus relentlessly on delivering customer value
• Collaborate across R&D to deliver full-scope solutions, not just ML components
• Rapidly prototype and prioritize algorithms based on user needs
• Build and scale ML systems using state-of-the-art techniques
• Lead efforts to acquire and manage high-quality datasets

What You'll Need To Be Successful

• Experience in writing production code with a focus on maintainability and performance.
• Experience training deep learning models, including expertise in model selection, training, optimization, and deployment.
• You have startup DNA: a growth mindset, a bias toward action, and a drive to take ownership of challenging projects with minimal guidance. You’re resourceful—when you hit a wall, you find a way around it, learn what you need, and keep moving forward.
• Computer vision expertise (or a strong foundation in deep learning from other domains, such as NLP). If you don’t have direct computer vision experience, a willingness to apply your deep learning knowledge to this area is important.
• Nice to have: Experience with cloud infrastructure, such as AWS, GCP, or Azure, and familiarity with scaling machine learning models in a cloud-based environment.

We’re a growing team that works collaboratively, is supportive of each other, and is highly energized by the opportunity for a large impact. We actively work to promote an inclusive environment, valuing passion and the ability to learn. You’re encouraged to apply even if your experience doesn’t precisely match the job description!
The following is a representative annual base salary range for this position within the Bay Area: $168,000 - $186,000. Job level and salary opportunities are evaluated through our interview process – we review the experience, knowledge, skills, and abilities of each applicant.
Instrumental is proud to offer a highly-rated variety of benefits, including health, vision, dental, commuter plans, and parental leave.