AS
Asapp-2Lead Machine Learning Engineer, Evaluations
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Before you apply
SalaryNo pay range posted
LocationMountain View
Work modehybrid
Typefull-time
SeniorityLead
DepartmentTechnology, Engineering
EquityIncluded
Company size51–200 people
PostedSep 11, 2026 · 1mo ago
Verified live3d ago
At a glanceSummarised by Seekless from the posting.
Deep, hands-on experience building and operating evaluation systems for modern ML/LLM/agentic systems
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
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
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
Skills
Python
AWS
Kubernetes
Docker
CI/CD
Kafka
Athena
LLM
ML
NLP
Benefits
Stock options
Medical insurance
Vision insurance
Dental insurance
401(k)
Fitness stipend
Wellness stipend
Mental wellbeing benefits
Professional development stipend
Parental leave
Paid time off
Sick leave
About the company
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.
About the role
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.
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
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
Legal
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 [email protected] to obtain assistance.