Machine Learning Engineer
Instrumental
Software Engineering
Palo Alto, CA, USA
USD 168k-270k / year
Posted on Jul 4, 2025
Machine Learning Engineer
Palo Alto, CA
Engineering
Hybrid
Full-time
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 and slow iteration.
Instrumental’s AI-powered platform changes that current reality. We give hardware teams real-time data and insights to catch and fix issues early—so they can build better products, faster, and with less waste. Leading brands like Meta, Bose, and Cisco use Instrumental to accelerate product development and improve yield at scale.
We’re a ~70-person, mission-driven team that values inclusivity, creativity, and impact. If that resonates with you, we'd love to chat!
About The Role:
We’re looking for a Machine Learning Engineer who’s passionate about turning cutting-edge research into customer impact. You’ll help build and scale Instrumental’s end-to-end ML systems — from prototyping to production — enabling our customers to identify and solve manufacturing issues faster than ever.
At Instrumental, ML engineers don’t just train models — they own the problem. You’ll have full lifecycle ownership: partnering with product and data teams to define features, exploring state-of-the-art methods, curating datasets, iterating rapidly, deploying at scale, and monitoring real-world performance. Your work will directly shape the product experience for some of the world’s most innovative hardware companies.
If you want meaningful ownership, tangible impact, and a collaborative environment that values learning and execution — this is the place.
What You'll Do:
- Design, build, and own ML pipelines end-to-end—from experimentation to deployment and impact measurement.
- Collaborate across R&D to deliver holistic solutions that combine ML, software, and user experience.
- Rapidly prototype algorithms and prioritize work based on real customer needs.
- Scale production ML systems using modern frameworks and best practices.
- Lead efforts to acquire, manage, and refine high-quality datasets for supervised and unsupervised learning.
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! We're additionally open to multiple levels — if you're a Senior, Staff, or Principal-level engineer, we'd also love to hear from you!
The following is a representative annual base salary range for this position within the Bay Area: $168,000 - $270,000. 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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Standard Questions: Are you legally authorized to work in the United States? *
Standard Questions: Will you now or in the future require sponsorship for employment visa status (e.g. H1-B visa status)? *
Can you briefly describe a time when you encountered a problem without an obvious solution? How did you decide what steps to take next?
Req ID: R16