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Remote Tesla Machine Learning Engineer Jobs in Wisconsin

Data Science Tutor

Madison, WI · Remote

$18 - $40/hr

Deep knowledge of statistical analysis, data wrangling, exploratory data analysis, machine learning, data visualization, SQL, Python or R programming, hypothesis testing, and communication of data ...

Data Science Tutor

Milwaukee, WI · Remote

$18 - $40/hr

Deep knowledge of statistical analysis, data wrangling, exploratory data analysis, machine learning, data visualization, SQL, Python or R programming, hypothesis testing, and communication of data ...

Python Tutor

Madison, WI · Remote

$18 - $40/hr

Emphasizes readable, maintainable code and connects Python to machine learning, web scraping, scientific computing, and DevOps applications. * Curriculum Awareness & Adaptive Instruction: Familiar ...

Python Tutor

Milwaukee, WI · Remote

$18 - $40/hr

Emphasizes readable, maintainable code and connects Python to machine learning, web scraping, scientific computing, and DevOps applications. * Curriculum Awareness & Adaptive Instruction: Familiar ...

Train customers' operators and technicians on machine setup, operation, change-over, and ... Provide technical support and assistance to customers via phone, remote connection, or on-site for ...

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Remote Tesla Machine Learning Engineer information

What does a Remote Tesla Machine Learning Engineer do?

A Remote Tesla Machine Learning Engineer is responsible for designing, developing, and deploying machine learning models to improve Tesla's products and services. Working from a remote location, they collaborate with teams to analyze large datasets, build predictive models, and optimize algorithms for applications such as autonomous driving, energy management, and manufacturing. They also ensure that machine learning solutions are scalable and meet Tesla's high standards for performance and safety.

What are some common challenges faced by Remote Tesla Machine Learning Engineers, and how can they be overcome?

Remote Tesla Machine Learning Engineers often face challenges such as collaborating across different time zones, ensuring effective communication with cross-functional teams, and maintaining access to high-performance computing resources. To overcome these, engineers typically use collaborative tools for code sharing and project management, participate in regular virtual meetings, and leverage Tesla's robust cloud infrastructure for experimentation and model training. Proactively seeking feedback and staying aligned with team goals are also key practices for success in this remote, fast-paced environment.

What are the key skills and qualifications needed to thrive as a Remote Tesla Machine Learning Engineer, and why are they important?

To thrive as a Remote Tesla Machine Learning Engineer, you need a strong background in computer science, mathematics, and machine learning principles, typically demonstrated through a relevant degree or equivalent experience. Proficiency with Python, TensorFlow or PyTorch, cloud platforms, and version control systems is crucial, and certifications in AI/ML can be advantageous. Exceptional problem-solving, communication, and self-motivation are important soft skills for collaborating remotely and tackling complex projects. These skills enable engineers to design, implement, and scale innovative AI solutions that drive Tesla's technology forward.

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

AspectRemote Tesla Machine Learning EngineerRemote Data Scientist
Required CredentialsDegree in Computer Science, Engineering, or related field; experience with ML frameworksDegree in Statistics, Mathematics, or related field; strong programming skills
Work EnvironmentCollaborates with engineering teams on autonomous systems and vehicle dataAnalyzes large datasets to extract insights for business or product decisions
Employer & Industry UsagePrimarily in automotive, tech, and autonomous vehicle sectorsAcross tech, finance, healthcare, and various industries

While both roles involve data analysis and machine learning, the Remote Tesla Machine Learning Engineer focuses on developing algorithms for autonomous vehicles, whereas the Remote Data Scientist analyzes data to inform business strategies. The roles share similar credentials but differ in application and industry focus.

What are popular job titles related to Remote Tesla Machine Learning Engineer jobs in Wisconsin? For Remote Tesla Machine Learning Engineer jobs in Wisconsin, the most frequently searched job titles are:
What cities in Wisconsin are hiring for Remote Tesla Machine Learning Engineer jobs? Cities in Wisconsin with the most Remote Tesla Machine Learning Engineer job openings:
VP of Enterprise Data, Analytics & AI

VP of Enterprise Data, Analytics & AI

TIDI PRODUCTS LLC

Neenah, WI • On-site, Remote

Full-time

Re-posted 11 days ago


Job description

Description
We are hiring a VP of Enterprise Data Analytics and AI!!
The Vice President of Enterprise Data, Analytics & AI is responsible for building TIDI's enterprise data foundation and advancing the analytics and AI capabilities it enables. This leader owns enterprise data strategy, governance, architecture, business intelligence, advanced analytics, data science, and the Databricks analytics platform.
The role will ensure internal and external data are trusted, connected, secure, and reusable so TIDI can move from retrospective reporting to predictive insight, intelligent automation, machine learning, and future AI-enabled decision support. In partnership with Technology Services, this leader will establish the integration and MCP frameworks that allow approved AI models, agents, applications, and workflows to access governed enterprise data.
This role is focused on data, platforms, analytics, and AI data foundations.
This position can work remotely with in the US, but must be willing to come into any of our locations, as needed.
ESSENTIAL DUTIES AND RESPONSIBILITIES:
• Execute TIDI's enterprise data, analytics, and AI data-foundation strategy and multi-year roadmap.
• Lead the Business Intelligence team and build capabilities across data engineering, advanced analytics, data science, and machine learning.
• Establish, scale, and govern the enterprise data and analytics platform in Databricks.
• Design an AI-ready architecture for structured and unstructured data, including reusable data products, semantic models, metadata, lineage, and business context.
• Establish standards for data quality, master data, governance, security, privacy, access, retention, observability, and regulatory compliance.
• Ensure data is prepared, governed, and accessible for reporting, predictive models, AI agents, retrieval, and automated workflows.
• Partner with Technology Services to implement MCP and other secure integration patterns connecting enterprise data, systems, analytical tools, models, and workflows.
• Relentlessly identify, evaluate, acquire, and integrate external data assets that improve market, customer, clinical, commercial, operational, and competitive decision-making.
• Build a portfolio of high-value analytics, data science, machine learning, and AI use cases tied to measurable business outcomes.
• Automate recurring data preparation, reporting, analysis, insight generation, and decision-support processes.
• Establish model and analytical governance, including validation, explainability, monitoring, performance, lifecycle management, and human oversight.
• Partner with business leaders to translate strategic questions into trusted data products, models, insights, and decisions.
• Define and monitor value, adoption, data quality, platform reliability, speed to insight, model performance, and reuse of analytical assets.
• Build, energize, and retain a high-performing, AI-enabled team that uses modern tools to increase speed, quality, and capacity.
• Manage data providers, technology partners, consultants, contracts, licenses, budgets, and platform investments.
CORE VALUES & GUIDING PRINCIPLES:
• Understands internal and external customers
• Assure a safe work environment
• Encourage individual development
• Demonstrates teamwork and flexibility/adaptability
• Demonstrates honesty
• Keep our commitments
• Think systemically and ensure constancy of purpose
• Lead with humility and respect every individual
• Focus on process, embrace scientific thinking, flow and pull value, assure quality at the source and seek perfection
EDUCATION & EXPERIENCE:
• Advanced degree in a relevant technical field.
• 12+ years of leadership experience across technology, engineering, digital product delivery, or AI-enabled transformation.
• Proven ability to lead cross-functional teams in delivering enterprise technology solutions.
• Experience using AI, automation, and modern engineering practices to improve business and delivery outcomes.
QUALIFICATIONS:
• Strong knowledge of agile delivery, software engineering, release management, quality practices, and governance.
• Executive-level communication skills and the ability to influence senior stakeholders.
• Track record of building high-performing teams and delivering results in complex, regulated environments.
• Experience with ERP-connected operations, quality systems, and responsible AI practices.
• Strong financial and vendor management acumen.
About TIDI Products...
TIDI Products is a market leading manufacturing of disposable infection prevention products and patient safety products, headquartered in Neenah, WI. We have manufacturing and distribution facilities in Neenah, WI, Newport News, VA, Norristown, PA, Littlestown, PA, United Kingdom and, Tijuana, MX and office space in Lincolnshire, IL. TIDI provides best in class products and service to major healthcare products distributors and users worldwide.
We Support Care Givers and Protect Patients!!
Disability Accommodation
For individuals with disabilities that need additional assistance at any point in the application and interview process, please email WIHR@tidiproducts.com or call 920-751-4300 x 4044.
Equal Opportunity Employer
TIDI Products is proud to be an equal opportunity employer and is committed to maintaining a diverse and inclusive work environment. All qualified applicants will receive considerations for employment without regard to race, color, religion, sex, age, disability, marital status, family.