Lead Machine Learning Engineer, Evaluations
- Location
- Mountain View · Hybrid
- Job type
- Full-time
- Level
- Director
- Education
- Bachelor's degree
- Listed
- 13 days ago
Skills & highlights for this role
- Machine Learning Evaluation Systems
- LLM/Agentic System Evaluation
- Evaluation Methodology Design
- Data Pipeline Design for ML Evaluation
- Annotation and Labeling Workflows
- Dataset Versioning and Quality Control
- Reproducible Benchmarking
- Python
- AWS
- Kubernetes and/or Docker
- Software Architecture
- Technical Leadership
- Technical Mentorship
Also useful
- Agentic AI Systems at Scale
- Voice/Audio Quality Evaluation
- Production LLM-Centric Services
- Large-Scale ML Experimentation
- Benchmarking and Simulation Frameworks
- Conversational/Customer-Support AI
- Containment Rate and Conversation Quality Metrics
What you'll do
- Help develop the technical roadmap and architecture for the evaluation platform, from offline benchmarking to online/production monitoring of agentic and LLM-based systems.
- Design eval methodologies appropriate to different stages of the pipeline: golden/regression test sets, human-in-the-loop review workflows, LLM-as-judge approaches, and automated metrics for task success, safety, and hallucinations.
- Build the data infrastructure evaluation depends on: annotation and labeling pipelines, dataset versioning, data quality checks, and tooling that lets researchers and product teams run and interpret experiments without needing platform team help.
- Partner closely with Research, Product, and Platform teams to productize experiments into robust AI solutions
- Represent the eval platform to stakeholders outside the immediate team- set expectations on what "good" looks like for a model/agent release, and report on platform health and coverage.
- Stay current with advancements in ML, NLP, voice, and LLM systems, and contribute actively to technical discussions across teams.
- Mentor and support other engineers through design reviews, feedback, and knowledge sharing.
What you'll need
- Deep, hands-on experience building and operating evaluation systems for modern ML/LLM/agentic systems- not just consuming existing eval tools.
- Demonstrated experience leading the technical direction of a project or small team: setting architecture, driving design reviews, and being accountable for a system's long-term health (not just shipping features).
- Strong architectural skills, with proven experience designing complex, data-intensive software systems and production experience with Python, AWS, Kubernetes, and/or Docker.
- Experience designing data pipelines for ML evaluation- labeling/annotation workflows, dataset versioning and quality control, and reproducible benchmarking.
- A Bachelor's Degree in CS or other related fields
- Demonstrated technical mentorship of junior and mid-level engineers, driving adoption of best practices and architectural alignment for scalability and extensibility.
- Desire to learn, teach, and collaborate closely with cross-functional peers.
What we'd like to see
- Experience building and evaluating agentic systems at scale.
- Experience with voice/audio quality evaluations.
- Production experience with LLM-centric services (e.g., inference, orchestration, evaluation, monitoring)
- Familiarity with large-scale ML experimentation, benchmarking, or simulation frameworks.
- Experience with conversational/customer-support AI domains (e.g., containment rate, conversation quality, goal completion).
- Knowledge of techniques for optimizing model architectures for faster inference.
- Experience with AWS, CI/CD, Kafka, Athena
Benefits include
- Competitive compensation with stock options
- Comprehensive medical, vision, and dental insurance
- 401k matching
- Fitness and wellness stipend
Mental well-being benefits
- Professional learning and development stipend
- Parental leave, including adoptive and foster parents
- 3 weeks paid time off (increases with tenure) along with sick leave, bereavement and jury duty
At ASAPP, our mission is simple
deliver the best AI-powered customer experience-faster than anyone else. To achieve that, we’re guided by principles that shape how we think, build, and execute. We value customer obsession, purposeful speed, ownership, and a relentless focus on outcomes. ASAPP’s AI Engineering team is seeking an enterprising, talented and curious machine learning engineer.
The AI Engineering team is responsible for working closely with the research and modeling teams to create state-of-the-art NLP models for specific tasks, and deploy them in a production setting designed to serve our customers at scale. We are looking for a Machine Learning Engineer to help build and evaluate the core intelligence behind our agentic AI systems. This role will play a key part in designing and owning evaluation frameworks that ensure quality, safety, and performance across complex agentic systems.
We're looking for a Lead Machine Learning Engineer to own and grow the evaluation platform that measures quality, safety, and performance across ASAPP's agentic AI systems- the infrastructure that tells us, with confidence, whether a model or agent change is actually an improvement before it reaches customers.
This a hybrid role with 10-12 days of in-office presence per month to balance flexibility with collaboration.
Equal opportunity and legal notices
ASAPP is committed to creating a diverse environment and is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, disability, age, or veteran status. If you have a disability and need assistance with our employment application process, please email us at to obtain assistance. #LI-SL1 #LI-Hybrid
From ASAPP's careers page, first listed on Rolev.ai on October 26, 2026. Rolev.ai is not the employer.
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Common questions
Where is the Lead Machine Learning Engineer, Evaluations job at ASAPP located?
This Lead Machine Learning Engineer, Evaluations position at ASAPP is located in Mountain View (Hybrid). Always check ASAPP's application page for specific state eligibility or relocation policies.
What qualifications are required for Lead Machine Learning Engineer, Evaluations at ASAPP?
For the Lead Machine Learning Engineer, Evaluations role, ASAPP highlights a bachelor's degree; experience with Machine Learning Evaluation Systems, LLM/Agentic System Evaluation, Evaluation Methodology Design, Data Pipeline Design for ML Evaluation, Annotation and Labeling Workflows, Dataset Versioning and Quality Control. Rolev.ai can score your existing resume against these requirements and show any skill gaps before you apply.
How do I apply for the Lead Machine Learning Engineer, Evaluations position at ASAPP?
This listing links directly to ASAPP's Lever application page. You can apply directly on ASAPP's site, or use Rolev.ai to check your resume fit, generate a zero-hallucination tailored resume and cover letter for this posting, and autofill the Lever application form in 1 click with the Rolev.ai Chrome extension. You always review the form and press Submit yourself.