5-7 years of experience in machine learning or related fields
Strong understanding of data quality and ML infrastructure
Experience with scientific benchmark design and delivery
Ability to collaborate with scientists and engineers
Proven track record of solving complex problems
Responsibilities
Analyze post-training data quality issues
Design and implement task and reward shaping strategies
Develop and maintain ML infrastructure
Create scientific benchmarks for evaluation
Deliver benchmarks efficiently while ensuring quality
Benefits
In-person collaboration in a dynamic San Francisco environment
Opportunity to work on cutting-edge problems at the intersection of biology and ML
Fast-paced hiring process with clear steps
Ownership of projects and creative problem-solving opportunities
Full Job Description
Engineer Researcher
The Role You will be working on problems in post-training, data quality, task and reward shaping, ML infrastructure, scientific benchmark design, and benchmark delivery. Challenges span understanding the intersection of biology and ML, collaborating directly with scientists, and maintaining quality at a fast cadence.
How we work
Our engineering team is in-person in San Francisco. We look for driven engineers who are excited to take ownership on hard problems and ship creative, useful solutions
Hiring process
Our process is typically completed within two weeks. • Round 1: Introduction • Round 2: Takehome Assessment • Round 3: Technical • Round 4: Final/ 3-Day Paid Onsite Project • Offer
