Sr.
Machine Learning Engineer, AutobidderThe mission of the Autobidder team is to accelerate the world's transition to sustainable energy by maximizing the value of storage and renewable assets.
We achieve this by building state-of-the-art software products for monetizing front-of-the-meter and behind-the-meter energy storage systems.
Our flagship product, Autobidder, is an end-to-end automation suite for wholesale electricity market participation of grid-connected batteries and renewable resources that maximize revenues by optimally bidding in all available revenue streams in these markets.
We are a multidisciplinary algorithmic trading team with expertise in machine learning, numerical optimization, software engineering, distributed systems, electricity markets, and trading.
We have a proven track record of operating storage assets and delivering high revenues in both utility-scale and Virtual Power Plant (VPP) settings.
Our products currently manage over 7GWh of energy storage worldwide and have returned over $420 million in trading profits, and we're slated for rapid growth on the horizon.
You will develop forecasting algorithms for Autobidder.
You will research, prototype, evaluate and productionize new forecasts for electricity prices and other relevant market outcomes.
You will ensure that forecasting improvements translate into trading revenue gains for our assets.
Your work will be critical in maintaining best-in-class performance of Autobidder.
You will own production systems and be responsible for their performance, reliability, and availability.
Your work will help proliferate the building of battery storage and renewable projects around the globe.
What to Expect You will develop forecasting algorithms for Autobidder.
You will research, prototype, evaluate and productionize new forecasts for electricity prices and other relevant market outcomes.
You will ensure that forecasting improvements translate into trading revenue gains for our assets.
Your work will be critical in maintaining best-in-class performance of Autobidder.
You will own production systems and be responsible for their performance, reliability, and availability.
Your work will help proliferate the building of battery storage and renewable projects around the globe.
What You'll Do Design, develop, and revolutionize our internal forecasting platformConduct creative research to identify new machine learning approaches that improve metrics and incorporate these into our platformIdentify and integrate new data sources to enhance model performanceDesign scalable and reliable data pipelines to productionize and monitor both new and existing modelsBecome an expert in electricity price formation and market dynamicsDeliver various types of electricity market-related forecasts including energy and ancillary service prices, load, regulation throughput, and reserve deployments for use in downstream algorithmsMentor and develop a growing team of exceptional machine learning engineers into one of the leading electricity market forecasting teamsCollaborate with optimization engineers, traders, market analysts, and software engineers to ensure forecasts drive end-to-end valueWhat You'll Bring Proficiency in Python with at least 4 years of experience in software development, familiarity with software development practices, writing production-quality code, and agile developmentExperience with a variety of forecasting algorithms and approaches, including statistical, regression, and deep learning algorithmsExperience with cloud-hosted systems and related tooling, including computing services AWS EC2, Google Compute Engine, container orchestration Kubernetes, Docker, and database and data warehouse platforms Amazon RDS, Google BigQueryExpertise with relevant Python libraries such as pandas, numpy, xgboost, lightgbm, pytorch, sklearn, plotly, seaborn, and streamlitDemonstrated experience in developing and maintaining production ML platformsIntrinsic motivation and passion for learning, collaboration, and working in the clean energy spaceDegree in Mathematics, Machine Learning, Statistics, or equivalent experienceDomain expertise in forecasting, analysis, or trading in electricity markets ERCOT, CAISO, PJM, AEMO, and UK National GridExperience in shipping production models in time series forecasting or reinforcement learningFamiliarity with forecasting libraries such as Nixtla, Pytorch-Forecasting or DartsCompensation and Benefits Along with competitive pay, as a full-time Tesla employee, you are eligible for the following benefits at day 1 of hire:
Aetna PPO and HSA plans > 2 medical plan options with $0 payroll deductionFamily-building, fertility, adoption and surrogacy benefitsDental (including orthodontic coverage) and vision plans, both have options with a $0 paycheck contributionCompany Paid (Health Savings Account) HSA Contribution when enrolled in the High Deductible Aetna medical plan with HSAHealthcare and Dependent Care Flexible Spending Accounts (FSA)401(k) with employer match, Employee Stock Purchase Plans, and other financial benefitsCompany paid Basic Life, AD&D, short-term and long-term disability insuranceEmployee Assistance ProgramSick and Vacation time (Flex time for salary positions), and Paid HolidaysBack-up childcare and parenting support resourcesVoluntary benefits to include: critical illness, hospital indemnity, accident insurance, theft & legal services, and pet insuranceWeight Loss and Tobacco Cessation ProgramsTesla Babies programCommuter benefitsEmployee discounts and perks programExpected Compensation $124,000 - $216,000/annual salary + cash and stock awards + benefits
Pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience.
The total compensation package for this position may also include other elements dependent on the position offered.
Details of participation in these benefit plans will be provided if an employee receives an offer of employment.
Tesla is an Equal Opportunity / Affirmative Action employer committed to diversity in the workplace.
All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, age, national origin, disability, protected veteran status, gender identity or any other factor protected by applicable federal, state or local laws.
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