ML Systems Engineer, Robotics & Autonomy

Tera AI; San Diego (CA); On-site; USD 100,000 - 130,000; Full time

Job summary

Tera AI in San Diego is seeking a technically adept individual to contribute to AI robotics projects. Candidates should possess a broad technical foundation in software engineering, with hands-on experience in building production-grade systems for robotics or autonomous platforms. Essential skills include deep proficiency in Python and experience with flight control software, evaluation pipelines, data ingestion, model optimization, and familiarity with DevOps tools. A creative and results-driven individual will thrive in this role.

Qualifications

• Broad technical foundation in software and systems engineering for robotics or autonomous platforms.
• Experience designing, building, and maintaining complex software systems.
• Deep proficiency in Python; C++ experience is a plus.

Skills

Systems engineering

Flight control software

Eval pipelines

Data pipelines

Model optimization

Programming in Python

Machine learning foundations

Backend development

Cloud infrastructure

Monitoring tools

Version control with Git

Familiarity with spatial data

Job description

Our team

Our team is composed of AI pioneers and leaders from Google X, Google Brain, and Unity. Several of us are repeat founders, with deep commercialization insights across multiple enterprise segments. We enjoy long, deep ideations around entirely unexplored AI use cases in autonomy (cars, drones, robots).

Who you are

• Curious: you have an innate curiosity for all things intellectual, and it’s something you can’t turn off. You obsess over finer details others miss.
• High intensity: you thrive in a high-stakes environment, and are driven by an innate obsession, not by others.
• Fast learner: you gravitate toward learning new things, and often find yourself learning more quickly than everyone around you.
• Driven by discomfort: you enjoy leaving your comfort zone and challenging yourself
• Creative: track record of solving hard problems with solutions worthy of academic papers
• Educator: you take pride in your ability to communicate complex topics clearly and have excellent speaking and writing skills.
• Zero ego: you don’t just take feedback, but truly see it as a gift. You don’t wait until feedback is given, but solicit it with every opportunity.
• Focused on results: you roll up your sleeves to help solve the most pressing problem on a given day, even if it has nothing to do with this job post.

Where you are

West or East Coast USA, San Diego Preferred

Technical skills

Broad technical foundation in software and systems engineering, with hands-on experience building and deploying production-grade systems for robotics or autonomous platforms.

• Systems engineering: experience designing, building, and maintaining complex software systems in robotics, autonomous vehicles, or drone platforms
• Flight control & autonomy: experience working with flight control software such as PX4 or ArduPilot is a strong plus
• Eval pipelines: experience designing and running evaluation pipelines for robotics or autonomous systems — including simulation, hardware-in-the-loop, and real-world benchmarking
• Data pipelines: experience writing preprocessing and ingestion pipelines for large-scale model training and fine-tuning (image foundation model)
• Model optimization: experience optimizing models for production deployment — quantization, pruning, distillation, TensorRT, ONNX, or edge inference frameworks
• Programming: deep proficiency in Python; C++ experience is a strong plus for real-time systems work
• ML foundations: solid understanding of deep learning theory and practice, especially computer vision and spatial reasoning (PyTorch, OpenCV)
• Backend: experience designing and building scalable, high-availability server-side systems (Python, NodeJS, or Golang)
• Cloud & infrastructure: familiarity with DevOps and infrastructure tooling — Docker, Kubernetes, GPU scheduling — on GCP or AWS
• Monitoring: experience with logging and observability tools such as DataDog, Sentry, and/or CloudWatch
• Version control: deep familiarity with Git and collaborative development workflows on GitHub or GitLab
• Domain-specific: familiarity with spatial data, geographic information systems, or spatial databases (PostGIS) is a plus