We're a Series A startup building a low-latency ML inference engine (and much more) as part of our Connected TV ad-buying platform. We're looking for Senior and Staff level Machine Learning Engineers with experience in Zig and Python to join our growing team!
What you'll do:
- Write production code in Zig, Python, and C
- Design and implement new ML products to deliver clear performance from connected TV advertising
- Serve as a technical lead and mentor to the team
Ideal candidate:
- Ability to write & review production-level code in Zig and Python
- Excellent writing skills
- Strong statistics and ML fundamentals
- Desire to work at a fast-growing Series A startup–working under uncertainty, owning and scaling new products, and an experimental and iterative development process
Why join us?
- An engineering culture optimized for async work and learning; remote-first, flexible, and humane.
- Competitive salary and equity options.
- An enormous diversity of high-leverage problems, from the CPU/GPU core level, through distributed systems, and up to the ML training stack and the experimentation around it. You can work at whatever level you think is interesting and leverages your skills the best.
If you're interested, apply on Greenhouse (https://grnh.se/3e08afa98us) or email me at mbilow[at]tvscientific[dot]com (I'm the Hiring Manager & Head of Data Science)
We're a Series A startup building a low-latency ML inference engine (and much more) as part of our Connected TV ad-buying platform. We're looking for Senior and Staff level Machine Learning Engineers with experience in Zig and Python to join our growing team!
What you'll do:
- Write production code in Zig, Python, and C
- Design and implement new ML products to deliver clear performance from connected TV advertising
- Serve as a technical lead and mentor to the team
Ideal candidate:
- Ability to write & review production-level code in Zig and Python
- Excellent writing skills
- Strong statistics and ML fundamentals
- Desire to work at a fast-growing Series A startup–working under uncertainty, owning and scaling new products, and an experimental and iterative development process
Why join us?
- An engineering culture optimized for async work and learning; remote-first, flexible, and humane.
- Competitive salary and equity options.
- An enormous diversity of high-leverage problems, from the CPU/GPU core level, through distributed systems, and up to the ML training stack and the experimentation around it. You can work at whatever level you think is interesting and leverages your skills the best.
If you're interested, apply on Greenhouse (https://grnh.se/3e08afa98us) or email me at mbilow[at]tvscientific[dot]com (I'm the Hiring Manager & Head of Data Science)