Tesla

Makes electric cars, robotaxis and grid batteries

Senior Machine Learning Engineer

Applied Machine LearningConfirmed live in the last 24 hours

Full-timeFremont, CA, USANo salary listedIn-person

About the Job

Requirements

A Bachelor's degree in Computer Science, Machine Learning, or a related field, or equivalent experience.
At least 5 years of experience building production backend systems, including at least 3 years shipping machine learning models or ML services.
Strong proficiency in Python for data processing, model development, and service development.
Experience with machine learning frameworks such as scikit-learn, PyTorch, or similar, including model evaluation and experiment tracking.
Experience designing and serving models behind APIs, including REST service design, versioning, and integration patterns.
Strong SQL skills and experience with relational databases such as SQL Server, including feature and data pipeline design.
Experience productionizing models with Docker, CI/CD, and cloud platforms; Azure is preferred.
Working knowledge of performance, reliability, logging, monitoring, and scalability for production machine learning systems.
Experience writing unit and integration tests for data pipelines, model logic, and services.
Experience mentoring engineers and driving technical decisions from problem framing through deployment.

Responsibilities

Design and build backend machine learning services and APIs that support forecasting, classification, anomaly detection, and decision-support use cases.
Own the path from data to production, including feature pipelines, model training, evaluation, deployment, and monitoring.
Partner with product and business stakeholders to define problems, success metrics, and how model outputs create value in existing workflows.
Integrate models into scalable backend systems, with clear contracts, versioning, and failure handling.
Improve model reliability, latency, and data quality in production, including logging, drift monitoring, and retraining strategies.
Review data, features, and model design with the team and provide constructive technical feedback.
Mentor engineers on machine learning engineering practices, testing, and production standards.
Share knowledge across software, data, and operations teams, and communicate trade-offs in plain language.

Desired Qualifications

Experience with Azure cloud platforms.

Category	Construction & Facilities
Location	Fremont, California
Requisition ID	288374
Type	Full-time

Job Description

<p>Design, build, and productionize backend machine learning services that support internal project management and operations applications. Work with development, data, and business teams to deliver models and APIs used by the Construction organization across project accounting, labor management, financial reporting, and insight and analytics.</p><p>The role is focused on backend ML systems: data pipelines, model training and serving, and reliable integration into production services. Own the technical path from problem definition through deployment, and help turn operational data into tools that improve decisions and workflows.</p>

Job Responsibilities

Design and build backend ML services and APIs that support forecasting, classification, anomaly detection, and decision-support use cases
Own the path from data to production, including feature pipelines, model training, evaluation, deployment, and monitoring
Partner with product and business stakeholders to define problems, success metrics, and how model outputs create value in existing workflows
Integrate models into scalable backend systems, with clear contracts, versioning, and failure handling
Improve model reliability, latency, and data quality in production, including logging, drift monitoring, and retraining strategies
Review data, features, and model design with the team and provide constructive technical feedback
Mentor engineers on ML engineering practices, testing, and production standards
Share knowledge across software, data, and operations teams, and communicate trade-offs in plain language

Job Requirements

Bachelor’s Degree in Computer Science, Machine Learning, or a related field, or equivalent experience
5+ years building production backend systems, including 3+ years shipping machine learning models or ML services
Strong proficiency in Python for data processing, model development, and service development
Experience with ML frameworks such as scikit-learn, PyTorch, or similar, including model evaluation and experiment tracking
Experience designing and serving models behind APIs, including REST service design, versioning, and integration patterns
Strong SQL skills and experience with relational databases such as SQL Server, including feature and data pipeline design
Experience productionizing models with Docker, CI/CD, and cloud platforms (Azure preferred)
Working knowledge of performance, reliability, logging, monitoring, and scalability for production ML systems
Experience writing unit and integration tests for data pipelines, model logic, and services
Experience mentoring engineers and driving technical decisions from problem framing through deployment

About the Company

Tesla

Makes electric cars, robotaxis and grid batteries

Tesla makes electric cars and batteries that store power for homes and utilities, and it develops self-driving software and humanoid robots. In 2023, its Model Y became the first electric vehicle to rank as the world's best-selling car. Buyers order the Model 3 sedan, Model Y SUV, or Cybertruck pickup directly from Tesla instead of through dealers, and they charge on its Supercharger fast-charging network. It also sells Megapack and Powerwall batteries, runs a robotaxi service, and charges drivers a monthly fee for self-driving software that still needs their supervision. Tesla was founded in 2003, with Elon Musk as its lead early investor and a recognized co-founder, and it is based in Austin, Texas.

Company size: 10,001+
Company stage: IPO
Headquarters: Austin, TX
Founded: 2003

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