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.
We are ~70 people – a small but mighty team.
We value an inclusive environment and actively work to promote diversity in our team.
If you are looking for a place to collaborate with a mission-oriented team to deliver an outsized impact on the manufacturing industry, we’d love to hear from you!
About The Role
We’re seeking a highly customer-centric Senior ML Engineer who will join our cross-functional engineering team.
You’ll be responsible for working with our talented engineers to build and maintain a highly scalable end-to-end ML production pipeline.
The role requires a mix of research and productization responsibilities, both delivered in a rapid, iterative clip.
What You’ll Do
Build and own machine learning pipelines end-to-end! For us, this means:
Maintain an obsessive focus on delivering value to our customers.
Maintain ownership of ML pipelines, all the way to surfacing the features to customers, and measuring their impact.
Partner closely with the entire R&D organization, working in a highly collaborative environment where you’ll be exposed to the entire scope of a deliverable rather than just the ML portion of the project.
Quickly prototype and iterate on new algorithmic concepts, and prioritize them based on customer needs.
Develop and deploy large-scale ML systems using the relevant state-of-the-art AI approaches to solve the problem.
Guide efforts to acquire high-quality datasets.
Manage and improve the ML pipeline, from data management, model management, and resource scheduling.
What you’ll need to be successful
Proven experience delivering ML features from research to production with a preference for candidates with an exposure to application development.
At least 3 years of delivering production systems in Python, Java or Scala.
Start-up or equivalent experience where you demonstrate strong attention to detail and ownership balanced with a scrappy, get-stuff-done, mentality.
3+ years of machine learning research and development experience; professional use of deep learning or computer vision is a bonus!
You have a computer science or related background with solid fundamentals in algorithms and the math behind them.
Feel at home communicating research and other complex ideas to a broad swath of the company including engineers and non-engineers.
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: $183,000 - $199,000.
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.
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