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Senior Tesla Machine Learning Engineer Jobs (NOW HIRING)

LHi Group Ltd

Senior Machine Learning Engineer

Austin, TX · On-site

$335K - $400K/yr

* Senior Machine Learning Engineers needed for high growth tech company * Austin, TX - must be willing to work in office 4 days a week * High competitive salary + equity + strong benefits Senior ...

Paylocity

Senior Machine Learning Engineer

$125K - $165K/yr

Senior Engineer Machine Learning Position Overview Paylocity is growing its Machine Learning Engineering organization! Our machine learning engineering team is responsible for developing ...

Paylocity

Senior Machine Learning Engineer

Schaumburg, IL · On-site

$120K - $159K/yr

Senior Engineer Machine Learning Position Overview Paylocity is growing its Machine Learning Engineering organization! Our machine learning engineering team is responsible for developing ...

Paylocity

Senior Machine Learning Engineer

Schaumburg, IL · On-site

$120K - $159K/yr

Senior Engineer Machine Learning Position Overview Paylocity is growing its Machine Learning Engineering organization! Our machine learning engineering team is responsible for developing ...

PROPRIUS

Senior Machine Learning Engineer

New York, NY · On-site

$114K - $157K/yr

Sr. Machine Learning Engineer Location: New York, NY Sponsorship: Yes Relocation: Yes Industry: Machine Learning A leading provider of AI is looking for a Sr. ML Engineer. Our client is an industry ...

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All JobsTesla Machine Learning Engineer JobsSenior Tesla Machine Learning Engineer Jobs

Senior Tesla Machine Learning Engineer information

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$59.5K

$126.6K

$183.5K

How much do senior tesla machine learning engineer jobs pay per year?

As of Aug 7, 2026, the average yearly pay for senior tesla machine learning engineer in the United States is $126,557.00, according to ZipRecruiter salary data. Most workers in this role earn between $104,500.00 and $143,500.00 per year, depending on experience, location, and employer.

How does a senior Tesla machine learning engineer typically collaborate with cross-functional teams?

As a Senior Machine Learning Engineer at Tesla, you will frequently work alongside software developers, data scientists, product managers, and hardware engineers. Collaboration is highly cross-functional, with regular meetings to align on project goals, data requirements, and model deployment strategies. You may be involved in translating business objectives into machine learning solutions, sharing insights with non-technical stakeholders, and refining algorithms based on feedback from various departments. This collaborative environment fosters innovation and ensures that machine learning models are well-integrated into Tesla's products and systems.

What are the key skills and qualifications needed to thrive as a senior Tesla machine learning engineer?

To thrive as a Senior Tesla Machine Learning Engineer, you need deep expertise in machine learning algorithms, strong programming skills in Python or C++, and a proven track record in deploying models at scale, often supported by an advanced degree in computer science or a related field. Familiarity with frameworks such as TensorFlow or PyTorch, experience working with large datasets, and cloud computing platforms are typically required, as well as knowledge of Tesla's proprietary systems. Exceptional problem-solving, collaboration, and communication skills distinguish top performers in this role. These abilities are crucial for developing advanced AI solutions that power Tesla's autonomous systems and for driving innovation in a highly competitive, fast-evolving environment.

What is the difference between Senior Tesla Machine Learning Engineer vs Data Scientist?

AspectSenior Tesla Machine Learning EngineerData Scientist
Required CredentialsBachelor's/Master's in CS, EE, or related; experience in ML frameworksBachelor's/Master's in CS, Statistics, or related; strong analytical skills
Work EnvironmentDevelops ML models for autonomous vehicles, energy, and manufacturingAnalyzes data to extract insights, supports product and business decisions
Employer & Industry UsageTesla, automotive, energy, AI projectsVarious industries including tech, finance, healthcare

While both roles involve working with data and algorithms, the Senior Tesla Machine Learning Engineer focuses on developing and deploying machine learning models for Tesla's products, especially autonomous systems. In contrast, a Data Scientist primarily analyzes data to inform business decisions across various industries. The ML Engineer role requires deeper expertise in machine learning frameworks and deployment, whereas Data Scientists focus more on statistical analysis and data visualization.

What does a senior Tesla machine learning engineer do?

A Senior Tesla Machine Learning Engineer leads the development and deployment of advanced machine learning models to improve Tesla’s products, such as Autopilot, Full Self-Driving, and manufacturing optimization. They collaborate with multidisciplinary teams to collect data, design algorithms, and ensure models are robust and scalable. In this role, engineers are expected to mentor junior staff, drive research initiatives, and help translate cutting-edge AI advancements into real-world Tesla applications.
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Senior Tesla Machine Learning Engineer jobs near you
Infographic showing various Senior Tesla Machine Learning Engineer job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 72% Full Time, 24% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $126,557 per year, or $60.8 per hour.

Sr. Machine Learning Engineer, Network Engineering

Tesla

Fremont, CA • On-site

$114K - $156K/yr

Full-time

Re-posted 11 days ago

Tesla rating

8.5

Company rating: 8.5 out of 10

Based on 681 frontline employees who took The Breakroom Quiz

1st of 44 rated automakers

Job description

Job Summary:
Tesla is seeking a highly skilled Senior Machine Learning Engineer to lead the development of a platform that integrates large scale LLM training with advanced network data processing and intelligent diagnostics. The role involves designing and maintaining machine learning pipelines, developing scalable backend services, and collaborating with networking experts to enhance operational capabilities.
Responsibilities:
• Design, build, and maintain pipelines for LLM pretraining, supervised fine-tuning (SFT), reward modeling, PPO/RLHF, and model evaluation
• Develop scalable backend services and distributed training infrastructure
• Build data-ingestion and transformation pipelines for networking datasets including device inventory, topology data, ARP/MAC tables, routing state, metrics, telemetry, and logs
• Normalize and model heterogeneous networking data to support ML workflows and agent inference
• Develop intelligent agent capabilities, including intent classification, context tracking, troubleshooting logic, and action-routing workflows
• Collaborate with networking domain experts to translate operational needs into model and platform capabilities
• Implement CI/CD, model versioning, orchestration, and production-grade deployment pipelines
• Drive architectural decisions to ensure scalability, modularity, reliability, and performance
Qualifications:
Required:
• 5+ years of experience in applied ML, ML systems, or backend platform engineering
• Strong experience with LLM training, including SFT, LoRA/PEFT, RLHF, reward modeling, and PPO
• Proficiency with PyTorch and distributed training technologies
• Solid backend engineering skills in Python, including APIs, microservices, data modeling, and containerization
• Strong understanding of networking fundamentals such as IP addressing, Ethernet, VLANs, routing protocols (BGP/OSPF/ISIS), and topology concepts
• Experience working with networking telemetry or operational data (SNMP, flow data, metrics, logs, routing/forwarding tables)
• Ability to interpret and model complex network states, device relationships, and diagnostic patterns
Company:
Tesla is an electric vehicle and clean energy company that provides electric cars, solar, and renewable energy solutions. Founded in 2003, the company is headquartered in Austin, USA, with a team of 10001+ employees. The company is currently Late Stage.

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