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# Sr. Machine Learning Engineer

- **Company:** Tesla, Inc.
- **Location:** Fremont, CA, United States
- **Experience:** Expert
- **Salary:** $124,000.0 - $258,000.0
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Microsoft Azure, Cloud Computing, Continuous Integration, Relational Databases, Database Queries, Python (Programming Language), Machine Learning, Microsoft SQL Server, Operational Data Store, Tensorflow, Azure Machine Learning, Service Design, Service Development Studio, Management of Software Versions, Data Logging, Data Processing, Pytorch, Model Validation, Backend, Build Management, Scikit Learn, Integration Tests, Information Technology, Machine Learning Operations, Drift Detection, Data Pipelines, Docker
- **Published:** October 31, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=4a12b01c896f3022

## About the Role

* 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

## Description

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.

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.
What You'll Do

 * 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