Sr. Machine Learning Engineer, Energy Optimization

Summary by AIEngineer.careers

Sr. Machine Learning Engineer, Energy Optimization is a Machine Learning Engineer role (full-time). with Tesla. in PALO ALTO, US. Compensation shown: $140K–$312K. Imported listing (source: scoutify.com). Apply on the employer's site (scoutify.com).

Imported listing (source: scoutify.com) · Apply on scoutify.com

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PALO ALTO · US

$140K–$312K

Full-time

SENIOR

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Imported job description

Sourced from scoutify.com

Tesla's Opticaster team builds applied machine learning systems that optimize battery charging and discharging across residential energy products, including Powerwalls, Megapacks, and Virtual Power Plants. As a Senior Machine Learning Engineer, you will own time-series forecasting models for load and solar, build evaluation and monitoring pipelines, and ship models to production at fleet scale. You will work across algorithm, software, firmware, and product teams to improve real-world energy decisions.

Responsibilities

Develop and productionize ML components in Opticaster, including time-series forecasting for load and solar
Implement model and algorithm changes in the production Python codebase with tests and safe rollout
Build and maintain evaluation pipelines using offline metrics, simulation, benchmarking, and regression detection
Diagnose field and simulation failures, distinguishing model/data issues from integration problems
Strengthen observability around production ML with monitoring, alerting, and tooling
Identify and resolve performance bottlenecks in ML pipelines and on-device runtime paths
Partner with algorithm, software, firmware, and product engineers to integrate ML into Tesla's energy ecosystem

Requirements

Degree in Computer Science, Engineering, Statistics, or a related technical field, or equivalent experience
Strong proficiency in Python within a large existing codebase
Experience shipping applied machine learning into production systems, including training, evaluation, deployment, and operation
Experience owning production software through design, implementation, debugging, and operation
Experience validating model changes with offline metrics, simulation, or regression-style evaluation
Experience with cloud and data technologies such as AWS, Spark, Airflow/Argo, Docker/Kubernetes, and CI/CD
Excellent communication and cross-functional collaboration skills

Nice to Have

Time-series forecasting experience
Experience with Rust
Experience with energy systems, battery storage, or real-world control systems

Benefits

medical insurancedental insurancevision insurance401k matchemployee stock purchase planlife insurancedisability insuranceflexible spending accountemployee assistance programpaid time offpaid holidayscommuter benefitsemployee discountsParental leavefertility benefitsadoption assistancepet insurance

Tech Stack

AirflowArgoAWSCI/CDDockerKubernetesPythonRustSparkTime-series Forecasting

Tesla

Austin · US · 134785+ employees

Tesla designs, manufactures, and sells electric vehicles, energy storage systems, and solar energy products. The company is focused on accelerating the world's transition to sustainable energy and is increasingly incorporating artificial intelligence into its vehicles and robotics.