Build, deploy, and maintain production classification and recommendation systems serving thousands of users
Design and implement ML pipelines for training, evaluation, and monitoring of traditional ML models
Integrate LLM APIs and vector databases into existing ML workflows to enhance product capabilities
Collaborate with product and engineering teams to translate business requirements into scalable ML solutions
Optimize model performance, system reliability, and inference latency across our ML stack

Requirements

5+ years deploying ML models in production (classification, recommendations, or similar)
Strong Python proficiency with ML libraries (scikit-learn, pandas, numpy) and deployment frameworks
Experience with ML infrastructure: model serving, monitoring, and data pipelines
Familiarity with foundation model APIs (OpenAI, Anthropic, etc.) and vector databases
Track record of building systems that handle real user traffic and data
U.S. citizenship with the ability to pass a Federal Background Check and Identity Verification.
While formal education is not a strict requirement, a Bachelor's or Master’s degree in Computer Science, Engineering, or a related field is preferred.

Benefits

Competitive salary with stock options in a rapidly growing, venture-backed company.
Comprehensive health plan, ensuring you and your loved ones are well taken care of.
Flexible work arrangements, including full remote work capabilities, to balance your professional and personal life.
Extensive professional development opportunities, providing a fast track for career advancement.

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

machine learningPythonscikit-learnpandasnumpymodel servingdata pipelinesLLM APIsvector databasesmodel optimization

Soft Skills

collaborationcommunicationproblem-solvingscalabilitysystem reliability

Certifications

Bachelor's degreeMaster's degree