8 hours ago
Base Salary
$285k - $340k/yr
Responsibilities
- Own the technical direction, architecture, interfaces, and engineering standards for the MLOps platform.
- Design and operate dataset versioning, lineage, splits, and labeling-integration workflows.
- Build and operate a model registry with versioned artifacts, metadata, evaluation results, lineage, and approval workflows.
- Define automated benchmarks, simulation rollouts, policy-gating harnesses, and metrics for model qualification.
- Own model packaging, serving, on-robot versioning, rollback, and observability from registered model to Apollo deployment.
- Coordinate deployment telemetry with Connect and Data Platform.
- Lead technical projects end to end and influence standards across Autonomy, Data Platform, TeleOp, and Training Infrastructure.
- Mentor MLOps engineers through code reviews, design reviews, and direct collaboration.
Requirements
- Deep proficiency in Python and at least one systems-level language: Go, Rust, or C++.
- End-to-end experience owning and delivering an MLOps platform that ships models to production, including datasets, experiment tracking, model registry, evaluation, and serving.
- Expertise with dataset versioning such as DVC, LakeFS, or Delta, and experiment tracking such as MLflow, W&B, or Determined.
- Strong experience designing service-oriented systems on Kubernetes and managing the contract between platform APIs and compute infrastructure.
- Experience defining evaluation and qualification frameworks for ML models in robotics, safety-critical, or production-customer-facing contexts.
- Experience leading technical projects through architecture, implementation, validation, and iteration.
- Demonstrated ability to lead by influence, establish adopted standards, and mentor engineers.
- Proficiency with cloud infrastructure, Docker, Git, and modern CI/CD workflows.
- Master’s degree in Computer Science, Machine Learning, or a related technical field preferred; a bachelor’s degree is considered with exceptional experience.
- At least 8 years of professional software engineering experience in ML platforms or related infrastructure, or at least 4 years of direct hands-on experience owning an MLOps platform that shipped models to production.
- Preferred experience includes deploying models to edge or embedded targets, reinforcement-learning training and evaluation infrastructure, humanoid robotics, dexterous manipulation, teleoperation data, simulation-in-the-loop evaluation, policy gating, shadow deployments, staged rollouts, and open-source MLOps contributions.
Benefits
- Direct-hire position.
- Annual base salary range of $285,000-$340,000.
- Equal employment opportunity workplace.
Categories
About Apptronik
Apptronik designs and manufactures AI-enabled humanoid robots, led by its Apollo platform, to automate tasks alongside people in manufacturing and logistics, with potential use in healthcare and homes. The privately held company is headquartered in Austin, Texas, and grew out of the University of Texas at Austin’s Human Centered Robotics Lab; its team previously worked on NASA’s Valkyrie robot. Apptronik’s business model centers on selling robots and the software and services needed to deploy them in industrial environments.