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
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-AG1 #LI-Hybrid
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
