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Tesla Estimator Jobs (NOW HIRING)

Tesla

AI Engineer, Manipulation, Optimus

Palo Alto, CA · On-site

$122K - $151K/yr

... estimation, Visual Odometry, SLAM, Structure from Motion, 3D Reconstruction Company : Tesla is an electric vehicle and clean energy company that provides electric cars, solar, and renewable energy ...

Russco, Inc.

Estimator

Fall River, MA · On-site

$70K - $100K/yr

Some current and past clients include General Cinema, Patriot Cinemas, Foot Locker, Gap, Tesla ... The Estimator will be team focused, detail oriented, and understand methods and processes for ...

Russco, Inc.

Estimator

Fall River, MA · On-site

$70K - $100K/yr

Some current and past clients include General Cinema, Patriot Cinemas, Foot Locker, Gap, Tesla ... The Estimator will be team focused, detail oriented, and understand methods and processes for ...

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Tesla Estimator information

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$31K

$73.3K

$127K

How much do tesla estimator jobs pay per year?

As of Aug 2, 2026, the average yearly pay for tesla estimator in the United States is $73,275.00, according to ZipRecruiter salary data. Most workers in this role earn between $53,000.00 and $86,500.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Tesla Estimator, and why are they important?

To thrive as a Tesla Estimator, you need expertise in cost estimation, project management, and a strong understanding of automotive repair or construction processes, often supported by relevant technical training or a degree. Familiarity with estimation software such as CCC ONE, Mitchell, or Audatex, and proficiency in using Tesla’s proprietary systems are typically required. Strong attention to detail, analytical thinking, and effective communication with customers and repair teams are valuable soft skills. These competencies ensure accurate assessments, cost control, and high customer satisfaction in Tesla’s fast-paced, quality-driven environment.

What is the difference between Tesla Estimator vs Solar Estimator?

AspectTesla EstimatorSolar Estimator
CredentialsSales or technical certifications, industry knowledgeSales or technical certifications, industry knowledge
Work EnvironmentOffice, on-site, customer consultationsOffice, on-site, customer consultations
Industry UsageTesla energy products, including solar and storageSolar energy systems, panels, and installations
Search IntentEstimating Tesla solar and energy projectsEstimating solar panel installations

Both Tesla Estimators and Solar Estimators focus on solar energy projects, often requiring similar certifications and working environments. Tesla Estimators specifically handle Tesla's energy products, including solar and storage solutions, while Solar Estimators may work with various brands and systems. Understanding these differences helps in choosing the right career path or service provider.

What are the main challenges Tesla Estimators face when coordinating with other departments during project planning?

Tesla Estimators often collaborate closely with engineering, procurement, and project management teams to ensure accurate cost projections and timelines. One common challenge is aligning estimates with rapidly evolving project specifications or changes in design, which requires constant communication and flexibility. Additionally, Estimators must balance cost efficiency with Tesla’s high standards for quality and innovation, making attention to detail and adaptability essential. Effective teamwork and proactive problem-solving are key to overcoming these challenges and delivering successful project outcomes.

What does a Tesla Estimator do?

A Tesla Estimator is responsible for evaluating and estimating the costs associated with projects, repairs, or installations related to Tesla vehicles, energy products, or infrastructure. This role involves reviewing project specifications, analyzing labor, materials, and time requirements, and preparing detailed cost estimates for clients or internal teams. Estimators collaborate with engineers, project managers, and suppliers to ensure accurate and competitive bids. Their work helps ensure projects are completed within budget while maintaining Tesla's high standards for quality and efficiency.
More about Tesla Estimator jobs
What cities are hiring for Tesla Estimator jobs? Cities with the most Tesla Estimator job openings:
What states have the most Tesla Estimator jobs? States with the most job openings for Tesla Estimator jobs include:
What job categories do people searching Tesla Estimator jobs look for? The top searched job categories for Tesla Estimator jobs are:
Tesla Estimator jobs near you
Infographic showing various Tesla Estimator job openings in the United States as of July 2026, with employment types broken down into 95% Full Time, 4% Part Time, and 1% Contract. Highlights an 92% Physical, 1% Hybrid, and 7% Remote job distribution, with an average salary of $73,275 per year, or $35.2 per hour.

Machine Learning Engineer, Model Quantization, Tesla AI

Tesla

Palo Alto, CA • On-site

Full-time

Re-posted 13 days ago

Tesla rating

8.5

Company rating: 8.5 out of 10

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.

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