Tesla is a leading company in the field of AI, focusing on building foundational models for real-world autonomy. The Machine Learning Engineer will be responsible for architecting and scaling ...
Tesla is a leading company in the field of AI, focusing on building foundational models for real-world autonomy. The Machine Learning Engineer will be responsible for architecting and scaling ...
Tesla is a leading electric vehicle manufacturer, and they are seeking a Machine Learning Engineer to join their Vehicle Controls and Navigation Algorithms team. The role involves developing accurate ...
Tesla is a leading electric vehicle manufacturer, and they are seeking a Machine Learning Engineer to join their Vehicle Controls and Navigation Algorithms team. The role involves developing accurate ...
Tesla is seeking a Staff Machine Learning Engineer for its Bottle Rocket team to develop innovative, data-driven solutions on Tesla's generative AI platform. The role involves leveraging machine ...
Tesla is seeking a Staff Machine Learning Engineer for its Bottle Rocket team to develop innovative, data-driven solutions on Tesla's generative AI platform. The role involves leveraging machine ...
Tesla is seeking a highly skilled Machine Learning Engineer to join the Supply Chain Engineering team. The role involves designing, developing, and deploying machine learning models to enhance supply ...
Tesla is seeking a highly skilled Machine Learning Engineer to join the Supply Chain Engineering team. The role involves designing, developing, and deploying machine learning models to enhance supply ...
Machine Learning Integration Engineer, Tesla AI
Palo Alto, CA · On-site
$122K - $164K/yr
As a Machine Learning Integration Engineer, you'll transform cutting-edge AI research into deployable, safety-critical systems that power Tesla's vehicles and humanoid robots, collaborating closely ...
Machine Learning Integration Engineer, Tesla AI
Palo Alto, CA · On-site
$122K - $164K/yr
As a Machine Learning Integration Engineer, you'll transform cutting-edge AI research into deployable, safety-critical systems that power Tesla's vehicles and humanoid robots, collaborating closely ...
Sr. Machine Learning Engineer, Network Engineering
Fremont, CA · On-site
$114K - $156K/yr
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 ...
Sr. Machine Learning Engineer, Network Engineering
Fremont, CA · On-site
$114K - $156K/yr
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 ...
Job Type Full-time Description Paylocity is an award-winning provider of cloud-based HR and payroll ... Machine Learning Engineer Position Overview Paylocity is growing its Machine Learning Engineering ...
Job Type Full-time Description Paylocity is an award-winning provider of cloud-based HR and payroll ... Machine Learning Engineer Position Overview Paylocity is growing its Machine Learning Engineering ...
Machine Learning Engineer
Carlsbad, CA · On-site
Machine Learning Engineer Position: Full time Location: Carlsbad office About Us: NTENT provides a Platform-as-a-Service (PaaS), allowing industry partners to customize, localize and integrate search ...
Machine Learning Engineer
Carlsbad, CA · On-site
Machine Learning Engineer Position: Full time Location: Carlsbad office About Us: NTENT provides a Platform-as-a-Service (PaaS), allowing industry partners to customize, localize and integrate search ...
We are looking for a Machine Learning Engineer to help us create artificial intelligence products. Machine Learning Engineer responsibilities include creating machine learning models and retraining ...
Quick apply
We are looking for a Machine Learning Engineer to help us create artificial intelligence products. Machine Learning Engineer responsibilities include creating machine learning models and retraining ...
Machine Learning Engineer Full-time Responsibilities * Build, maintain, and improve efficient and reliable data mining and machine learning models. * Design, implement and tune machine learning ...
Machine Learning Engineer Full-time Responsibilities * Build, maintain, and improve efficient and reliable data mining and machine learning models. * Design, implement and tune machine learning ...
Detroit, MI- Onsite Type: Full-time Security Clearance: No clearance required, must be clearable. The Machine Learning Engineer will be an essential member of the Research and Development Team, where ...
Detroit, MI- Onsite Type: Full-time Security Clearance: No clearance required, must be clearable. The Machine Learning Engineer will be an essential member of the Research and Development Team, where ...
Machine Learning Engineer Position: Full time Location: Carlsbad office About Us: NTENT provides a Platform-as-a-Service (PaaS), allowing industry partners to customize, localize and integrate search ...
Machine Learning Engineer Position: Full time Location: Carlsbad office About Us: NTENT provides a Platform-as-a-Service (PaaS), allowing industry partners to customize, localize and integrate search ...
Machine Learning Engineer
Minneapolis, MN · On-site
We are adding a Machine Learning Engineer to our team! This person will play a key role in ... you? * Full-time salaried consultant position * A true stake in success. SDG is an ESOP - 100 ...
Machine Learning Engineer
Minneapolis, MN · On-site
We are adding a Machine Learning Engineer to our team! This person will play a key role in ... you? * Full-time salaried consultant position * A true stake in success. SDG is an ESOP - 100 ...
We are adding a Machine Learning Engineer to our team! This person will play a key role in ... you? * Full-time salaried consultant position * A true stake in success. SDG is an ESOP - 100 ...
We are adding a Machine Learning Engineer to our team! This person will play a key role in ... you? * Full-time salaried consultant position * A true stake in success. SDG is an ESOP - 100 ...
As a Machine Learning Engineer, you will work with complex datasets, design and optimize models, and help bring intelligent solutions into production. You will collaborate with software engineers and ...
New
As a Machine Learning Engineer, you will work with complex datasets, design and optimize models, and help bring intelligent solutions into production. You will collaborate with software engineers and ...
New
The Machine Learning Engineer will develop and optimize machine learning models to enhance healthcare operations and collaborate with cross-functional teams to integrate solutions into existing ...
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Machine Learning Engineer
Schaumburg, IL · On-site
Machine Learning Engineer Position Overview Paylocity is growing its Machine Learning Engineering organization! Our machine learning engineering team is responsible for developing infrastructure and ...
Quick apply
Machine Learning Engineer
Schaumburg, IL · On-site
Machine Learning Engineer Position Overview Paylocity is growing its Machine Learning Engineering organization! Our machine learning engineering team is responsible for developing infrastructure and ...
Systems Engineer. We seek Machine Learning Engineer | Data Management & Business Intelligence ... Our growing list of benefits currently includes the following for Full-Time Employees:
Systems Engineer. We seek Machine Learning Engineer | Data Management & Business Intelligence ... Our growing list of benefits currently includes the following for Full-Time Employees:
We seek Machine Learning Engineer | Data Management & Business Intelligence - Data Scientist ... Our growing list of benefits currently includes the following for Full-Time Employees:
We seek Machine Learning Engineer | Data Management & Business Intelligence - Data Scientist ... Our growing list of benefits currently includes the following for Full-Time Employees:
Machine Learning Engineer
New York, NY · On-site
... Machine Learning Engineer while also providing a truly unparalleled educational experience ... You'll be paired with full-time employees who act as mentors, collaborating with you on real-world ...
Machine Learning Engineer
New York, NY · On-site
... Machine Learning Engineer while also providing a truly unparalleled educational experience ... You'll be paired with full-time employees who act as mentors, collaborating with you on real-world ...
Full Time Tesla Machine Learning Engineer information
See salary details
$31.5K - $46.2K
1% of jobs
$46.2K - $61K
1% of jobs
$61K - $75.7K
5% of jobs
$75.7K - $90.4K
6% of jobs
$102.6K is the 25th percentile. Wages below this are outliers.
$90.4K - $105.1K
14% of jobs
$105.1K - $119.9K
14% of jobs
The median wage is $127.2K / yr.
$119.9K - $134.6K
18% of jobs
$134.6K - $149.3K
14% of jobs
$152.3K is the 75th percentile. Wages above this are outliers.
$149.3K - $164K
12% of jobs
$164K - $178.8K
11% of jobs
$178.8K - $193.5K
5% of jobs
$31.5K
$128.8K
$193.5K
How much do full time tesla machine learning engineer jobs pay per year?
As of Aug 1, 2026, the average yearly pay for full time tesla machine learning engineer in the United States is $128,769.00, according to ZipRecruiter salary data. Most workers in this role earn between $101,500.00 and $155,000.00 per year, depending on experience, location, and employer.
What is the difference between Full Time Tesla Machine Learning Engineer vs Full Time Tesla Data Scientist?
| Aspect | Full Time Tesla Machine Learning Engineer | Full Time Tesla Data Scientist |
|---|---|---|
| Required Credentials | Bachelor's or Master's in CS, ML, or related field; experience with ML frameworks | Bachelor's or Master's in CS, Statistics, or related; strong analytical skills |
| Work Environment | Develops ML models for autonomous driving, energy, and manufacturing | Analyzes data to inform business decisions, optimize processes |
| Employer & Industry Usage | Tesla's AI and autonomous vehicle teams | Tesla's data analytics and business intelligence teams |
While both roles require strong technical skills and experience with data, Tesla Machine Learning Engineers focus on developing and deploying ML models for autonomous systems, whereas Tesla Data Scientists analyze data to support strategic decisions. The roles overlap in skills but differ in application and focus.
More about Full Time Tesla Machine Learning Engineer jobs
What cities are hiring for Full Time Tesla Machine Learning Engineer jobs? Cities with the most Full Time Tesla Machine Learning Engineer job openings:
What are the most commonly searched types of Tesla Machine Learning Engineer jobs? The most popular types of Tesla Machine Learning Engineer jobs are:
What states have the most Full Time Tesla Machine Learning Engineer jobs? States with the most job openings for Full Time Tesla Machine Learning Engineer jobs include:
What job categories do people searching Full Time Tesla Machine Learning Engineer jobs look for? The top searched job categories for Full Time Tesla Machine Learning Engineer jobs are:
- On Call Machine Learning Ops Engineer
- Full Time No Experience Machine Learning
- Graduate Machine Learning Engineer
- Director Google Machine Learning Engineer
- Machine Learning Operations Engineer
- Machine Learning Engineer Hybrid
- Freelance Google Machine Learning Engineer
- Entry Level Amazon Opt
- Weekend Machine Learning
- Home Based Nvidia Machine Learning
Full-time
Re-posted 12 days ago
Tesla rating
8.5
Based on 679 frontline employees who took The Breakroom Quiz
1st of 44 rated automakers
Job description
Job Summary:
Tesla is a leading company in the field of AI, focusing on building foundational models for real-world autonomy. The Machine Learning Engineer will be responsible for architecting and scaling quantization pipelines for multi-modal foundation models, optimizing inference latency and power consumption for various applications including self-driving cars and robots.
Responsibilities:
• Architect and scale quantization pipelines (both Post-Training Quantization and Quantization-Aware Training) for massive multi-modal foundation models that fuse vision, prediction, and decision-making. You will optimize inference latency, memory bandwidth utilization, and power consumption for self-driving cars, Optimus robots, and digital agents operating at enterprise scale
• Innovate quantization-aware-training recipes and algorithms that tackle complex optimization challenges inherent to low-precision training
• Push the limits of low-precision AI: Research and implement advanced low-bitweight post-training quantization techniques to address hard algorithmic problems such as activation outlier mitigation, KV cache compression, and optimal layer-wise bit-allocation while strictly maintaining model accuracy
• Collaborate closely with AI compiler, inference engine, and silicon teams to ensure models are architected to maximally utilize underlying hardware capabilities by co-designing quantization-friendly architectures, hardware-aware sparsity patterns, and mixed low-precision kernels
• Collaborate across perception, planning, robotics, digital agents, and infrastructure teams to move models from research to fleet-wide, robot-wide, and enterprise-wide deployment
Qualifications:
Required:
• Degree or equivalent experience in Computer Science, Machine Learning, Robotics, Computer Vision, or related quantitative field
• 2+ years of hands-on experience training, optimizing, and deploying large-scale quantized deep learning models
• Strong technical understanding of the challenges inherent to quantizing large transformer architectures, including mitigating massive activation outliers, KV cache quantization, and maintaining the numerical stability of attention mechanisms at low precision
• Deep expertise in the theory and low-level implementation of modern quantization algorithms (e.g., GPTQ, AWQ, SmoothQuant, OmniQuant)
• Experience with low-level numerics and emerging data formats (e.g., FP8, INT4, W4A8, W8A8, micro-scaling/MX formats) and their trade-offs regarding latency, memory bandwidth, and model fidelity
• Rigorous understanding of computer architecture and the roofline model. Familiarity with how to optimize for memory hierarchies, minimize SRAM/DRAM data movement, and efficiently map quantized GEMMs and memory-bound operators to custom silicon
• Proficiency in writing custom CUDA/Triton kernels, implementing custom autograd functions (e.g., Straight-Through Estimators), and manipulating PyTorch computational graphs (e.g., FX tracing, torch.compile)
• Strong software engineering skills — clean, production-grade Python/C++ code that ships reliably at scale
• Proven ability to turn cutting-edge research into robust, real-world systems that improve safety, capability, efficiency, or digital productivity
• Passion for Tesla’s mission and excitement about deploying AI that moves both the physical and digital worlds forward
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.
Tesla is a leading company in the field of AI, focusing on building foundational models for real-world autonomy. The Machine Learning Engineer will be responsible for architecting and scaling quantization pipelines for multi-modal foundation models, optimizing inference latency and power consumption for various applications including self-driving cars and robots.
Responsibilities:
• Architect and scale quantization pipelines (both Post-Training Quantization and Quantization-Aware Training) for massive multi-modal foundation models that fuse vision, prediction, and decision-making. You will optimize inference latency, memory bandwidth utilization, and power consumption for self-driving cars, Optimus robots, and digital agents operating at enterprise scale
• Innovate quantization-aware-training recipes and algorithms that tackle complex optimization challenges inherent to low-precision training
• Push the limits of low-precision AI: Research and implement advanced low-bitweight post-training quantization techniques to address hard algorithmic problems such as activation outlier mitigation, KV cache compression, and optimal layer-wise bit-allocation while strictly maintaining model accuracy
• Collaborate closely with AI compiler, inference engine, and silicon teams to ensure models are architected to maximally utilize underlying hardware capabilities by co-designing quantization-friendly architectures, hardware-aware sparsity patterns, and mixed low-precision kernels
• Collaborate across perception, planning, robotics, digital agents, and infrastructure teams to move models from research to fleet-wide, robot-wide, and enterprise-wide deployment
Qualifications:
Required:
• Degree or equivalent experience in Computer Science, Machine Learning, Robotics, Computer Vision, or related quantitative field
• 2+ years of hands-on experience training, optimizing, and deploying large-scale quantized deep learning models
• Strong technical understanding of the challenges inherent to quantizing large transformer architectures, including mitigating massive activation outliers, KV cache quantization, and maintaining the numerical stability of attention mechanisms at low precision
• Deep expertise in the theory and low-level implementation of modern quantization algorithms (e.g., GPTQ, AWQ, SmoothQuant, OmniQuant)
• Experience with low-level numerics and emerging data formats (e.g., FP8, INT4, W4A8, W8A8, micro-scaling/MX formats) and their trade-offs regarding latency, memory bandwidth, and model fidelity
• Rigorous understanding of computer architecture and the roofline model. Familiarity with how to optimize for memory hierarchies, minimize SRAM/DRAM data movement, and efficiently map quantized GEMMs and memory-bound operators to custom silicon
• Proficiency in writing custom CUDA/Triton kernels, implementing custom autograd functions (e.g., Straight-Through Estimators), and manipulating PyTorch computational graphs (e.g., FX tracing, torch.compile)
• Strong software engineering skills — clean, production-grade Python/C++ code that ships reliably at scale
• Proven ability to turn cutting-edge research into robust, real-world systems that improve safety, capability, efficiency, or digital productivity
• Passion for Tesla’s mission and excitement about deploying AI that moves both the physical and digital worlds forward
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.