Software Engineer - Axion Data Engine and ML Ops

Applied Intuition•Sunnyvale, CA

1d•Onsite

About The Position

The Axion Data team is building the data engine to train perception models. We build the means to run models at the edge such as Automatic Target Recognition (ATR) models, then backhaul data to our cloud pipeline that ingests and manages this data to enable the continual improvement of these models. As an engineer experienced in MLOps, you will be responsible for both our edge application which runs perception stacks and our cloud data engine which ingests video data to run the next iteration of the model before we deploy it back down to the edge. This includes optimizing our ability to run these models on both the edge and the cloud, building MLOps tooling to gain insight and visibility into the pipeline for our stakeholders.

Requirements

5+ years of relevant work experience
Familiarity with modern ML infrastructure, data-centric AI approaches and running large-scale jobs on GPUs
Created or worked on microservices and/or databases for data-oriented software
A hunger to learn and grow into a position of ownership and impact on a new product team
U.S. citizenship (legally required) and eligibility to obtain a security clearance

Nice To Haves

Full-stack experience
React, TypeScript
Python, Golang or similar
Experience with Docker, Kubernetes, Opensearch and Postgres
Direct experience with foundation models, including LLMs and VLMs, for data automation tasks
Background in autonomous driving or robotics perception
Experience with active learning, auto-labeling, or human-in-the-loop ML systems

Responsibilities

Construct optimized data pipelines to run ML models
Evolve our data engine architecture to scale high-fidelity labels, reduce annotation costs, and accelerate ML iteration cycles
Integrate foundation models (LLMs, VLMs, and multimodal models) to automate and enhance labeling, quality assurance, and data discovery
Leverage software-in-the-loop and hardware-in-the-loop testing
Interact with the DoD customer to understand their use cases, requirements, and triage needs during field events to deliver a superior customer experience