Lead Machine Learning Engineer

ASAPP; New York (NY); On-site; USD 170,000 - 190,000; Full time

Benefits offered by this job

Stock options

Medical + Vision + Dental

401k matching

Wellness stipend

Mental health support

Job summary

ASAPP in New York City is seeking a Machine Learning Engineer to help build and evaluate the core intelligence behind our agentic AI systems. You’ll design evaluation frameworks and turn research ideas into production-grade ML solutions that scale for customers.

You’ll collaborate with Research, Product, and Platform teams, mentor junior engineers, and stay at the forefront of NLP, LLMs, and AI systems. Hybrid work requires 10–12 days in office monthly to balance collaboration with flexibility.

Qualifications

• NLP and ML systems expertise with LLM/agentic experience.
• Production-grade Python, AWS, Kubernetes, and Docker experience.
• Bachelor’s degree in CS or related field.
• Ability to mentor junior engineers and drive best practices.

Responsibilities

• Design and build ML evaluation systems for agentic/LLM architectures.
• Translate research ideas into production-grade ML systems with measurable impact.
• Collaborate with Research, Product, and Platform teams to productize experiments.
• Mentor engineers and support design reviews and knowledge sharing.
• Stay current with ML/NLP/LLM advancements and contribute to technical discussions.

Skills

NLP

LLM systems

Production-grade ML

Python

AWS

Kubernetes

Docker

Mentorship

Education

Bachelor’s Degree in CS

Tools

Docker

Kubernetes

AWS

CI/CD

Kafka

Athena

Job description

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. This a hybrid role with 10-12 days of in‑office presence per month to balance flexibility with collaboration.

What you’ll do

• Design and development of ML evaluation systems for agentic and LLM-based architectures
• Translate research ideas into production‑grade ML systems with measurable impact
• Partner closely with Research, Product, and Platform teams to productize experiments into robust AI solutions
• Stay current with advancements in ML, NLP, and LLM systems, contributing actively to technical discussions across teams
• Mentor and support other engineers through design reviews, feedback, and knowledge sharing.

What you’ll need

• Deep experience in NLP and modern ML systems, including hands‑on experience with LLM‑based or agentic systems.
• Strong architectural skills, with proven experience designing complex software systems along with production experience with Python, AWS, Kubernetes, and/or Docker.
• Experience implementing technical solutions, tackling tough engineering problems to help build our products and a deep passion for Machine Learning.
• A Bachelor’s Degree in CS or other related fields
• Desire to learn new things, work closely with peers from different teams, and open to teach and learn from others.
• Demonstrate proficiency in the technical mentorship of junior and mid-level engineers, driving the adoption of best practices and ensuring architectural alignment for scalability and extensibility.

What we’d like to see

• Experience building and evaluating agentic systems at scale.
• Production experience with LLM‑centric services (e.g., inference, orchestration, evaluation, monitoring)
• Familiarity with large-scale ML experimentation, benchmarking, or simulation framework
• Knowledge of techniques for optimizing model architectures for faster inference
• Experience with AWS, CI/CD, Kafka, Athena

$170,000 - $190,000 a year

Compensation package also includes a performance bonus on top of the listed salary range

Separately, we also offer a compelling equity grant comprised of stock options

Benefits Include

• Competitive compensation with stock options
• Comprehensive medical, vision, and dental insurance
• 401k matching
• Fitness and wellness stipend
• Mental well-being benefits