Tesla
Sr. Machine Learning Engineer, Charging Data Modeling
Tesla, Palo Alto, California, United States, 94306
Sr. Machine Learning Engineer, Charging Data Modeling
Overview
We are the charging-data-modeling team that uses data analytics and machine learning to bridge the engineering, service, deployment and operation of Teslas charging infrastructure and to enhance the charging experience worldwide. With over 70,000 Superchargers and several thousand destination charging sites around the world, Teslas charging solution aims to accelerate the worlds transition to sustainable energy by enabling electric mobility without compromises. We use large-scale data analysis and machine learning models to decide the deployment of the charging infrastructure in terms of location, timing and quantity. We build algorithms that power the vehicle UI features for enhancing the charging experience while minimizing the charging costs to customers. What You'll Do Use statistical analysis to extract insights on fleet usage, trends, performance Improve data-driven decision making through rigorous data analysis, machine learning modeling and clear communication with stakeholders Leverage insights to inform planning and optimization of the EV infrastructure Design, prototype, and production algorithms that drives customer UI features, and pricing signals Build reliable, fast, and dynamic data tools, and data pipelines
What You'll Bring
Degree in a quantitative field (e.g., Math, Statistics, Computer Science, Data Science, Engineering) or equivalent in experience and evidence of exceptional ability Strong programming skills with a solid foundation in data structures and algorithms Proficiency in data analysis, modeling in Python Proficiency in SQL relational databases and/or NoSQL databases Experience with statistical data analysis and machine learning Background in machine learning with experience in using both supervised and unsupervised models is preferred Experience with timeseries or geospatial datasets is preferred Experience with experiment design and causal inference methods is preferred Experience with Spark, Hadoop and streaming data is preferred Quantitative projects available online (GitHub, blog posts, etc.) are preferred
Benefits
Aetna PPO and HSA plans > 2 medical plan options with $0 payroll deduction Family-building, fertility, adoption and surrogacy benefits Dental (including orthodontic coverage) and vision plans, both have options with a $0 paycheck contribution Company Paid (Health Savings Account) HSA Contribution when enrolled in the High Deductible Aetna medical plan with HSA Healthcare and Dependent Care Flexible Spending Accounts (FSA) 401(k) with employer match, Employee Stock Purchase Plans, and other financial benefits Company paid Basic Life, AD&D, short-term and long-term disability insurance Employee Assistance Program Sick and Vacation time (Flex time for salary positions), and Paid Holidays Back-up childcare and parenting support resources Voluntary benefits to include: critical illness, hospital indemnity, accident insurance, theft & legal services, and pet insurance Weight Loss and Tobacco Cessation Programs Tesla Babies program Commuter benefits Employee discounts and perks program
Expected Compensation
$124,000 - $240,000/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. Seniority level
Mid-Senior level
Employment type
Full-time
Job function
Engineering and Information Technology
Industries
Motor Vehicle Manufacturing Renewable Energy Semiconductor Manufacturing Utilities
Referrals increase your chances of interviewing at Tesla by 2x Get notified about new Machine Learning Engineer jobs in Palo Alto, CA. #J-18808-Ljbffr
We are the charging-data-modeling team that uses data analytics and machine learning to bridge the engineering, service, deployment and operation of Teslas charging infrastructure and to enhance the charging experience worldwide. With over 70,000 Superchargers and several thousand destination charging sites around the world, Teslas charging solution aims to accelerate the worlds transition to sustainable energy by enabling electric mobility without compromises. We use large-scale data analysis and machine learning models to decide the deployment of the charging infrastructure in terms of location, timing and quantity. We build algorithms that power the vehicle UI features for enhancing the charging experience while minimizing the charging costs to customers. What You'll Do Use statistical analysis to extract insights on fleet usage, trends, performance Improve data-driven decision making through rigorous data analysis, machine learning modeling and clear communication with stakeholders Leverage insights to inform planning and optimization of the EV infrastructure Design, prototype, and production algorithms that drives customer UI features, and pricing signals Build reliable, fast, and dynamic data tools, and data pipelines
What You'll Bring
Degree in a quantitative field (e.g., Math, Statistics, Computer Science, Data Science, Engineering) or equivalent in experience and evidence of exceptional ability Strong programming skills with a solid foundation in data structures and algorithms Proficiency in data analysis, modeling in Python Proficiency in SQL relational databases and/or NoSQL databases Experience with statistical data analysis and machine learning Background in machine learning with experience in using both supervised and unsupervised models is preferred Experience with timeseries or geospatial datasets is preferred Experience with experiment design and causal inference methods is preferred Experience with Spark, Hadoop and streaming data is preferred Quantitative projects available online (GitHub, blog posts, etc.) are preferred
Benefits
Aetna PPO and HSA plans > 2 medical plan options with $0 payroll deduction Family-building, fertility, adoption and surrogacy benefits Dental (including orthodontic coverage) and vision plans, both have options with a $0 paycheck contribution Company Paid (Health Savings Account) HSA Contribution when enrolled in the High Deductible Aetna medical plan with HSA Healthcare and Dependent Care Flexible Spending Accounts (FSA) 401(k) with employer match, Employee Stock Purchase Plans, and other financial benefits Company paid Basic Life, AD&D, short-term and long-term disability insurance Employee Assistance Program Sick and Vacation time (Flex time for salary positions), and Paid Holidays Back-up childcare and parenting support resources Voluntary benefits to include: critical illness, hospital indemnity, accident insurance, theft & legal services, and pet insurance Weight Loss and Tobacco Cessation Programs Tesla Babies program Commuter benefits Employee discounts and perks program
Expected Compensation
$124,000 - $240,000/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. Seniority level
Mid-Senior level
Employment type
Full-time
Job function
Engineering and Information Technology
Industries
Motor Vehicle Manufacturing Renewable Energy Semiconductor Manufacturing Utilities
Referrals increase your chances of interviewing at Tesla by 2x Get notified about new Machine Learning Engineer jobs in Palo Alto, CA. #J-18808-Ljbffr