Sr. Manager, Service Engineering Intelligence & Analytics

Tesla Energy's deployed fleet — Powerwall, Megapack, solar, and charging — is growing fast. Service Engineering exists for one goal: maximize fleet health with minimal intervention. The Service Engineering Intelligence & Analytics (SEIA) team turns the fleet's telemetry, service actions, customer reports, and escalations into the pipelines, detection models, dashboards, and SI tools Tesla can use to optimize fleet performance.

You will lead that team — a 20+ person multidisciplinary organization spanning data engineering, machine learning, GenAI, and analytics across Palo Alto and Amsterdam. You own the data and intelligence backbone behind how Service senses a problem, diagnoses it, and acts on it with the right part, in the right place, with the right capability, at the right time.

You lead from the user and the mission, not the tooling: you can see where fleet-health intelligence needs to go next and build the team to get there. You will be measured by outcomes — product uptime, time-to-detect, diagnostic coverage, and cost to serve — not by dashboards shipped. You stay technical enough to set architecture and keep the trust of your most senior engineers while growing both the people and the platform.

- Set the multi-year vision and technical strategy for how Service senses, diagnoses, and acts on fleet health — turning fleet telemetry and service signals into the detection models, pipelines, dashboards, and SI tools the organization relies on
- Lead, grow, and coach a 20+ person multidisciplinary organization spanning data engineering, machine learning, GenAI, and analytics across multiple sites — building growth paths on both technical and leadership tracks
- Own the fleet-health data and intelligence platform end to end — real-time and batch detection, the data backbone, hardware performance, and the GenAI / Service Intelligence tooling products — as a durable, self-service asset rather than a collection of one-off products
- Bind the team's work to operational outcomes. You will measure uptime and availability against SLAs, time-to-detect, diagnostic coverage, and cost. You will set the KPIs that prove the fleet actually got healthier, not just that tickets closed
- Partner with the engineering verticals (Residential, Industrial, Charging), field operations, support, and the programs and parts organizations so every detection flows into the right action with the right part, place, capability, and time
- Set the engineering bar for architecture, software development lifecycle, data quality and governance, reliability, and on-call — staying hands-on enough to review modeling approaches
- Represent Service Engineering's intelligence and analytics strategy to leadership and cross-functional partners like firmware, platform engineering, product management, devOps, finance, design engineering, and myriad other software groups

- Degree in Computer Science, Engineering, Data Science, or equivalent
- 10+ years in data, ML, or software, including 5+ years leading engineering teams, ideally as a manager of both managers and senior individual contributors
- Proven record building and scaling data and ML platforms that ship to production and drive real decisions — pipelines, detection and anomaly models, and the infrastructure behind them
- Fluency across the modern data and ML stack — streaming and batch pipelines, warehousing, ML systems with feedback loops, and GenAI / LLM applications — with enough depth to guide architecture and interrogate the data yourself
- Track record of tying data and analytics directly to operational outcomes in a hardware, IoT, fleet, or reliability context — uptime, predictive maintenance, diagnostic coverage, or cost
- Starts from the user and the fleet-health mission, not the tech — can name where the team needs to go and carry a multidisciplinary, multi-site org through ambiguity to get there
- Extreme ownership and the ability to influence without authority — partners across engineering, field, and programs, and holds the line on data integrity and measurable impact

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 $140,000 - $312,000/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.