Imagine writing software with no debugger, no logging, and only getting to compile it three times before you need to ship millions of copies. That’s what building electronics products is like for hardware, quality, and process engineers. As a result of this data- and insight-poor environment, companies waste significant time, money, and material. Instrumental’s manufacturing AI and data platform solves this problem for the most admired hardware companies in the world.
Instrumental’s mission is to drive manufacturing efficiencies through technology that empowers teams to build products better, faster, and with less waste. Brands like Meta, Bose, Cisco, and SolarEdge use our technology to optimize their manufacturing processes and deliver superior products in less time. We start by collecting data that no one else can; then we use machine learning and visualizations to automatically identify defects and help companies understand their assembly processes. As a result, product and process problems are caught and solved earlier, before they create delays and cost millions.
What the role is about
We’re seeking a customer-centric, hands-on machine learning leader to help accelerate our technology development and productization efforts. The role will lead a team of talented ML engineers and partner closely with the R&D leadership to build and execute against our product roadmap. You’ll operate in a highly cross-functional environment, working closely with our product, edge computing, and web application teams to deliver iterative and increasing value for our customers. The key to success will be balancing research and productization while removing roadblocks that slow the team down.
What you will do
- Maintain an obsessive focus on the customer experience by working cross-functionally to understand customer pain points; and turn those challenges into impact-driven ML research and solutions.
- Keep our ML engineers focused, productive, and growing while nurturing and expanding our culture of innovation rapidly.
- Own the overall output and quality of our ML efforts; iterate rapidly to drive increasing value. Candidates must feel equally comfortable using quantitative and qualitative data to drive quality.
- Partner closely with the R&D leadership team to drive ML initiatives; collaborate closely with customers and our customer success teams to solve real-world customer challenges.
- Actively contribute towards projects as well as identify improvements in our ML infrastructure.
We’d love to chat if you have
- Passion for understanding and solving customer problems. You’re obsessed about the impact our technology has and the value we bring to our customers.
- A proven track record of building and shipping production software for 7+ years with at least 3 years working exclusively in ML. Bonus if you have past experience working in a full-stack software capacity.
- 3+ years of experience developing, leading, coaching, and mentoring engineers. Formal leadership experience is a bonus!
- Real-world experience communicating to different stakeholders. You know how to communicate with engineers, product management, executives, customers, etc.
- Demonstrated history of successfully productizing ML research for customers.
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: $223,000 - $243,000. 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.
This role requires authorization to access information that is subject to U.S. export control restrictions.
