Research Engineer

adaption•San Jose, CA

2d•Hybrid

About The Position

We are obsessed with efficiency - allowing for real-time evolution of AI depends on making adaptable data and algorithms extremely efficient. The ideal candidate brings an expertise in building the pipeline that retrains or fine-tunes a model from production data instead of just querying one. We’re looking for an engineer who thrives at the intersection of applied research and building real-world products. You’ll drive the design and implementation of adaptable data strategies. You’ll work directly with the founding team, contributing to both the research direction and the product vision. This role demands technical excellence and a passion for delivering real-world impact.

Requirements

Bachelor’s degree in Computer Science, Machine Learning, or a related field
3-4 years of experience in machine learning, applied research, or systems-level engineering for artificial intelligence.
Demonstrated experience closing the loop from production signal back into model retraining or fine-tuning.
Experience with online learning, reinforcement learning, or efficient ML architectures.
Strong software engineering skills and familiarity with Python.
Exposure to working with observability tools in the past (e.g. OpenTelemetry, Docker, Grafana).
Excellent communication skills and ability to align technical work with high-level goals.
A mindset of ownership, curiosity, and a bias toward action.
Great teammates who make work feel lighter and aren't afraid to go out on a limb with bold ideas.
Adaptable.

Responsibilities

Lead the development and deployment of efficient, adaptive ML systems in real production environments.
Own implementation of data products at Adaption.
Drive the design and implementation of adaptable data strategies.
Contribute to both the research direction and the product vision.