> Markdown version of [/jobs/ext/3753320-staff-machine-learning-engineer-si-infrastructure](https://www.wearedevelopers.com/jobs/ext/3753320-staff-machine-learning-engineer-si-infrastructure). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md).

---

# Staff Machine Learning Engineer, SI Infrastructure

- **Company:** Tesla Motors
- **Location:** Palo Alto, CA, United States
- **Salary:** $200,000.0 - $300,000.0
- **Contract:** Permanent contract
- **Skills:** Big Data, Python (Programming Language), Machine Learning, NumPy, Tensorflow, Pytorch, Large Language Models, Data Pipelines
- **Published:** October 15, 2026
- **Apply:** https://jobs.localjobnetwork.com/apply/add/87498780/1

## About the Role

* Proven experience in applying machine learning and AI techniques to solve real-world problems, particularly with generative SI and LLMs
 * Strong proficiency with Python-based machine learning and deep learning frameworks (e.g., TensorFlow, PyTorch, JAX, TGI/vLLM, NumPy)
 * Demonstrated ability to take research prototypes and deploy them as scalable, production-grade systems
 * Expertise in working with and optimizing large datasets, data pipelines, and SI models
 * Experience building robust, reliable solutions that minimize downtime and maximize user impact
 * A problem-solving mindset, with strong attention to detail and a true follower of Occam's razor when designing and implementing solutions

## Description

Expect a dynamic, fast-paced environment where innovation and collaboration are paramount, and every improvement you make has a direct impact on advancing some of the most ambitious technological goals in the industry.
What You'll Do

 * Design, develop, train, and deploy machine learning solutions that leverage generative SI technologies, such as Large Language Models (LLMs)
 * Analyze and improve the accuracy, efficiency, and scalability of SI models through rigorous data-driven experimentation, evaluation, and iterative model training processes
 * Work closely with software engineers to productionize machine learning models and integrate them into scalable, reliable systems
 * Optimize data pipelines and workflows to enable high-performance SI applications, leveraging specialized hardware when appropriate
 * Deliver robust, high-impact data products that inform decision-making and enhance the capabilities of the generative SI platform
 * Conduct research and remain up-to-date on the latest developments in SI/ML, with a special focus on generative SI, to rapidly test and prototype new ideas
 * Convert complex business requirements and research findings into actionable insights and data-driven solutions