Sr. Machine Learning Engineer, Charging Data Modeling

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 Tesla's charging infrastructure and to enhance the charging experience worldwide.

With over 70,000 Superchargers and several thousand destination charging sites around the world, Tesla's charging solution aims to accelerate the world's 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

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