Senior ML Engineer - NLP/LLM Production Systems (Hybrid)

ASAPP; Mountain View (CA); Hybrid; USD 170,000 - 190,000; Full time

Benefits offered by this job

Stock options

Comprehensive medical, vision, dental

401k matching

Wellness stipend

Learning and development stipend

Parental leave (adoptive/foster)

3 weeks paid time off plus leave

Job summary

ASAPP in Mountain View is seeking an experienced Machine Learning Engineer to design and evaluate core NLP and agentic AI systems. You will work with Research and Platform teams to deploy scalable ML solutions and ensure performance, safety, and quality across production systems.

The role is hybrid with 10-12 days in-office per month, offering a competitive salary with equity options. A Bachelor's degree and strong Python/AWS/Kubernetes/Docker experience are required.

Qualifications

• Bachelor's degree in CS or related field.
• Experience with NLP and modern ML systems.
• Production experience with Python, AWS, Kubernetes, or Docker.
• Ability to mentor junior engineers.
• Willingness to learn and collaborate across teams.

Responsibilities

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

Skills

NLP & ML

Python

AWS

Kubernetes

Docker

Software architecture

Mentorship

Education

Bachelor's degree in CS or related field

Tools

Python

AWS

Kubernetes

Docker

Job description

ASAPP in Mountain View is seeking an experienced Machine Learning Engineer to design and evaluate core NLP and agentic AI systems. You will work with Research and Platform teams to deploy scalable ML solutions and ensure performance, safety, and quality across production systems.

The role is hybrid with 10-12 days in-office per month, offering a competitive salary with equity options. A Bachelor's degree and strong Python/AWS/Kubernetes/Docker experience are required.