Sr. Machine Learning Engineer

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. 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 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 Benefits Along with competitive pay, as a full-time Tesla employee, you are eligible for the following benefits at day 1 of hire: Medical plans > 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 Accounts) HSA Contribution when enrolled in the High-Deductible 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 (90 day waiting period) Employee Assistance Program Sick and Vacation time (Flex time for salary positions, Accrued hours for Hourly 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 Earned Wage Access: Real-time pay access paid daily, subject to eligibility and schedule (applicable for below Sr.

Managers levels) Expected Compensation $124,000 - $258,000/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.