ASAPP

SaaS AI agents for customer service

Staff Machine Learning Engineer - Evaluations

Natural Language Processing & LLMsUpdated on Nov 12

Full-time

About the Job

Requirements

Deep, hands-on experience building and operating evaluation systems for modern machine learning, large language model, and agentic systems, rather than only using existing evaluation 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.
Strong architectural skills and proven experience designing complex, data-intensive software systems.
Production experience with Python, AWS, Kubernetes, and/or Docker.
Experience designing data pipelines for machine learning evaluation, including labeling and annotation workflows, dataset versioning and quality control, and reproducible benchmarking.
A Bachelor's degree in Computer Science or another related field.
Demonstrated technical mentorship of junior and mid-level engineers, driving adoption of best practices and architectural alignment for scalability and extensibility.

Responsibilities

Lead the technical roadmap and architecture for the evaluation platform, from offline benchmarking to online and production monitoring of agentic and large language model-based systems.
Design evaluation methodologies for different pipeline stages, including golden and regression test sets, human-in-the-loop review workflows, large language model-as-judge approaches, and automated metrics for task success, safety, and hallucinations.
Build the data infrastructure that evaluation depends on, including annotation and labeling pipelines, dataset versioning, data quality checks, and tools that let researchers and product teams run and interpret experiments without platform-team assistance.
Partner with Research, Product, and Platform teams to turn experiments into robust AI solutions.
Represent the evaluation platform to stakeholders outside the immediate team, set expectations for model and agent release quality, and report on platform health and coverage.
Stay current with advancements in machine learning, natural language processing, voice, and large language model systems, and contribute to technical discussions across teams.
Mentor and support other engineers through design reviews, feedback, and knowledge sharing.

Desired Qualifications

Experience building and evaluating agentic systems at scale.
Experience with voice and audio quality evaluations.
Production experience with large language model-centric services, such as inference, orchestration, evaluation, and monitoring.
Familiarity with large-scale machine learning experimentation, benchmarking, or simulation frameworks.
Experience with conversational and customer-support AI domains, such as containment rate, conversation quality, and goal completion.
Knowledge of techniques for optimizing model architectures for faster inference.
Experience with AWS, continuous integration and continuous delivery, Kafka, and Athena.
Experience managing a small team of engineers in a fast-paced environment.

Salary Range: 190000 to 220000 (Currency: USD) (Pay period: per-year-salary)

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 Staff 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

Lead 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

Experience managing a small team of engineers in a fast-paced environment

Benefits

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

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. #LI-SL1 #LI-Hybrid

About the Company

ASAPP

SaaS AI agents for customer service

ASAPP provides software-as-a-service AI tools to boost customer service. Its main offering is a fully conversational AI voice and chat agent that can transcribe calls, automate call summaries, and generate automated responses to help agents. The product works by running an AI-powered agent in customer service conversations, delivering real-time or post-call transcription, producing summaries, and suggesting or sending automated replies, with the entire system delivered through a scalable subscription model. The company differentiates itself by serving high-volume call centers and service-focused enterprises with an emphasis on efficiency and data-driven insights, backed by ongoing software updates and a suite of productivity tools. Its goal is to improve human performance in customer service, reducing costs, speeding resolutions, and increasing customer satisfaction through AI-assisted processes.

Company size: 201-500
Company stage: Series C
Total funding: $380M
Headquarters: New York City, New York
Founded: 2014

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