We’re hiring a Staff Machine Learning Engineer for Autobidder, Tesla's industry leading platform for trading batteries (utility scale and VPPs) in electricity markets (like ERCOT, CAISO, etc.). The role involves building scalable ML pipelines and models to forecast electricity price and related market quantities. These forecasts feed into bid optimization algorithms that generate revenue-maximizing bids which are then programmatically submitted to the market.
Autobidder operates several GWh of battery storage assets globally, offering a unique opportunity to make a large-scale impact and advance renewable energy adoption.
What we’re looking for: • Expertise in time-series forecasting. • Experience with Python and production ML systems. • Passion for renewable energy and a desire to become a domain expert in electricity markets.
Location: Palo Alto, CA
More details and to apply: https://www.tesla.com/careers/search/job/staff-machine-learn...
Stanford Research Computing (https://srcc.stanford.edu) is a collaboration between University IT and the Vice Provost and Dean of Research. We operate HPC environments for researchers, we do one-time consultations on projects (from software and pipelines, to data management, to physical building design and fit-out), and we provide contract support for individual Labs, Departments, and Schools.
We have two open positions:
• Research Computing Manager: Our current IC:Manager ratio is 7, which is too high, so we're hiring another manager for our group! You'll oversee a number of ICs, help them plan & prioritize their work, make policy decisions, and contribute to Research Computing's strategic direction. You'll also be interacting with groups throughout the University, as a service provider and as a policy maker. More info: http://phxc1b.rfer.us/STANFORD0_zSLT
• Research Storage Consultant: We have lots of storage environments (both on-prem & cloud); it can be confusing to identify which is the best for a given purpose, and how to take full advantage of it. Your job will be to help Students & Faculty figure out what storage is best to use, and get them started on using it! More info: http://phxc1b.rfer.us/STANFORDWvaSLS
If you don't already live in the Bay Area, we provide a relocation incentive. Depending on where you live, we provide free transit passes. Unfortunately, if you drive, you will have to pay for parking for the days you're on-site. There is some on-call around the holidays. We get a 403(b) match, good healthcare, and 30+ days off per year (holidays + vacation). All Benefits are all publicly documented at https://cardinalatwork.stanford.edu/benefits-rewards. If you have questions, feel free to reply here or email me (the info is in my profile)!
Foundry is building the future of AI infrastructure with our Cloud Platform, providing self-serve access to high-performance GPU compute for training, fine-tuning, and serving AI models. We’re simplifying infrastructure for dynamic AI workflows, enabling AI practitioners to focus on innovation, not infrastructure.
We’re well-funded ($80M, Series A), growing quickly, and looking for talented people to join our team.
Here are some of the roles we’re hiring for:
- Senior Software Engineer, Full Stack
Design and build our compute marketplace and products. Focus on both backend and frontend technologies, REST APIs, and microservice architecture. [6+ years experience with Typescript, Python, etc.]
- Infrastructure Engineer
Architect and deploy infrastructure solutions. Work with Kubernetes, Terraform, and AWS products to optimize cloud performance. [6+ years experience in infrastructure and automation. Experience with Python, Kubernetes, and Terraform.]
- Site Reliability Engineer (SRE)
Build reliable systems for AI workflows. Work across Kubernetes, Linux, and cloud services to ensure platform scalability and performance. [Focus on system design and reliability.]
- Software Engineer, Security Engineer
Design and implement security strategies for our AI/ML infrastructure. Build systems that keep our platform secure at scale.
Learn more about us and apply: www.mlfoundry.com/company Or email us directly: careers@mlfoundry.com