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Senior Tesla Machine Learning Engineer Jobs in Missouri

PhD in STEM +0 years of relevant experience or equivalent related work experience * 5+ years of experience in data engineering, machine learning engineering, or related roles * Data Pipeline ...

$80K - $110K/yr

Our partner is looking for a Senior Geospatial Machine Learning Engineer based in Netherlands. Join a fully remote, mission-driven climate technology environment where machine learning and satellite ...

Experience using machine learning frameworks * Solid software engineering fundamentals * Proven ability to own and deliver ML components or services within cross-functional teams * Familiarity with ...

New

Job Summary The Machine Learning Engineer will tackle challenging problems and create scalable machine learning systems and platforms that make an impact on millions of users. This role will work ...

As a Machine Learning Integration Engineer, you will help rapidly prototype, mature, and monitor ML/CV solution that are integral to Turion's Space Domain Awareness data products. You will work on ...

Walmart is seeking a Senior Machine Learning Engineer to design, develop, and deliver scalable ML solutions that address complex business challenges. This role involves collaborating with cross ...

We are looking for a strong Staff Machine Learning Engineer who has the passion to develop AI driven intelligent products for the Associate Productivity and Experience team, with the ability to ...

Staff, Machine Learning Engineer

Noel, MO · On-site

$130K - $260K/yr

We are looking for a strong Staff Machine Learning Engineer who has the passion to develop AI driven intelligent products for the Associate Productivity and Experience team, with the ability to ...

We are looking for a strong Staff Machine Learning Engineer who has the passion to develop AI driven intelligent products for the Associate Productivity and Experience team, with the ability to ...

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Senior Tesla Machine Learning Engineer information

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.

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.

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 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 are the most commonly searched types of Tesla Machine Learning Engineer jobs in Missouri?

The most popular types of Tesla Machine Learning Engineer jobs in Missouri are:

What are popular job titles related to Senior Tesla Machine Learning Engineer jobs in Missouri?

For Senior Tesla Machine Learning Engineer jobs in Missouri, the most frequently searched job titles are:

What cities in Missouri are hiring for Senior Tesla Machine Learning Engineer jobs?

Cities in Missouri with the most Senior Tesla Machine Learning Engineer job openings:

Machine Learning Engineer

California, MO • On-site

$130 - $190/hr

Other

Posted 20 days ago


Job description

Responsibilities
  • build dynamic troubleshooting agents that understand networks
  • solve unstructured production log data complexities
  • optimize hardware utilization for data collection
  • automate synthetic datasets creation
  • architect data infrastructure for real-time network failures analysis
  • design and scale automated pipelines transforming raw production logs into insights
  • develop systems generating synthetic data for edge cases learning
  • tackle unique network complexity problems
  • optimize data collection and hardware utilization
Requirements
  • Bachelor's degree in STEM and 5+ years of relevant experience
  • Master's degree in STEM and 3+ years of relevant experience
  • PhD in STEM +0 years of relevant experience or equivalent related work experience
  • 5+ years of experience in data engineering, machine learning engineering, or related roles
  • Data Pipeline experience, designing and scaling data pipelines for unstructured or semi-structured data, including ingestion, cleansing, and auditing
  • ML Infrastructure experience working with ML data workflows, including dataset creation, labeling, and evaluation
  • Experience with Python and data processing frameworks (e.g., Spark, Beam, Ray)
  • Experience with ML systems and tools, such as training pipelines and model evaluation frameworks
  • Experience with human-in-the-loop ML systems, active learning, weak supervision or self-evolving agents (preferred)
  • Exposure large language models, computer vision, or speech datasets (preferred)
  • Experience building internal tools or platforms used by annotation or operations teams (preferred)
Hard Skills
  • Data Engineering
  • Machine Learning Engineering
  • Data Pipeline
  • Data Processing
  • Synthetic Data Creation
  • Real-Time Analysis
  • Network Troubleshooting
  • Data Cleansing
  • Model Evaluation
  • Active Learning
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