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Remote Tesla Machine Learning Engineer Jobs in Wisconsin

Serve Robotics

$225K - $260K/yr

Master's or PhD in Computer Science, Robotics, Electrical Engineering, Machine Learning, or a closely related technical discipline. * Minimum of 5 years of professional experience developing ...

Varsity Tutors

Machine Learning Tutor

Madison, WI · Remote

$18 - $40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Varsity Tutors

Machine Learning Tutor

Milwaukee, WI · Remote

$18 - $40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Urus Group LP

Senior AI/ML Engineer

Watertown, WI · On-site +1

$99K - $136K/yr

... machine learning to modern generative AI, choosing the simplest tool that solves the problem ... Feature-engineering and data preprocessing for both structured farm data and unstructured sources.

AgSource

Senior AI/ML Engineer

Watertown, WI · On-site +1

$99K - $136K/yr

... machine learning to modern generative AI, choosing the simplest tool that solves the problem ... Feature-engineering and data preprocessing for both structured farm data and unstructured sources.

Qualysoft

... to-End Machine-Learning-Workflows von der Entwicklung bis zum produktiven Einsatz ... Remote bevorzugt, gelegentliche Vor-Ort-Termine nach Absprache 400 - 450 a day Aufgaben Aufbau und ...

Qualysoft

... Betrieb skalierbarer Machine-Learning- und LLM-Losungen auf Azure Databricks von der ... Hybrid - ca. 50 % vor Ort in Wien, ca. 50 % remote Projektsprache: Deutsch und Englisch Aufgaben: ...

CSAA

Job Title Software Engineer III - AI/ML Platform Operations - Remote Requisition Number R7739 ... platforms, machine learning workloads, cloud infrastructure, and data integrations. * Lead root ...

CSAA

Job Title Software Engineer III - AI/ML Platform Operations - Remote Requisition Number R7739 ... platforms, machine learning workloads, cloud infrastructure, and data integrations. * Lead root ...

CSAA

Job Title Software Engineer III - AI/ML Platform Operations - Remote Requisition Number R7739 ... platforms, machine learning workloads, cloud infrastructure, and data integrations. * Lead root ...

CSAA

Job Title Software Engineer III - AI/ML Platform Operations - Remote Requisition Number R7739 ... platforms, machine learning workloads, cloud infrastructure, and data integrations. * Lead root ...

SysLogic, Inc.

Senior Data Engineer

Brookfield, WI · Remote

$100K - $136K/yr

Knowledge to leverage Artificial Intelligence and Machine Learning capabilities within Microsoft ... This remote role is only open to individuals that reside in one of the following states at the time ...

SysLogic, Inc.

Senior Data Engineer

Brookfield, WI · On-site +1

$100K - $136K/yr

Knowledge to leverage Artificial Intelligence and Machine Learning capabilities within Microsoft ... This remote role is only open to individuals that reside in one of the following states at the time ...

Johnson Controls

AI Engineer

Glendale, WI · On-site +1

This is a hybrid/remote role that is flexible on location so long as there is flexibility to travel ... Strong foundation in machine learning fundamentals - supervised/unsupervised learning, time-series ...

Qualysoft

Hybrid - ca. 50 % vor Ort in Wien, ca. 50 % remote Projektsprache: Deutsch und Englisch Aufgaben: ... Microsoft Foundry, Azure Cognitive Services, Azure Machine Learning Erfahrung in der Entwicklung ...

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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 the key skills and qualifications needed to thrive as a remote Tesla machine learning engineer?

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 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 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 job categories do people searching Remote Tesla Machine Learning Engineer jobs in Wisconsin look for?

The top searched job categories for Remote Tesla Machine Learning Engineer jobs in Wisconsin 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:

Remote Tesla Machine Learning Engineer jobs near you

Lead Machine Learning Engineer

Serve Robotics

On-site, Remote

$225K - $260K/yr

Full-time

Re-posted 7 days ago

Job description

At Serve Robotics, we're reimagining how things move in cities. Our personable sidewalk robot is our vision for the future. It's designed to take deliveries away from congested streets, make deliveries available to more people, and benefit local businesses.
The Serve fleet has been delighting merchants, customers, and pedestrians along the way in Los Angeles, Miami, Dallas, Atlanta and Chicago while doing commercial deliveries. We're looking for talented individuals who will grow robotic deliveries from surprising novelty to efficient ubiquity.
Who We Are
We are tech industry veterans in software, hardware, and design who are pooling our skills to build the future we want to live in. We are solving real-world problems leveraging robotics, machine learning and computer vision, among other disciplines, with a mindful eye towards the end-to-end user experience. Our team is agile, diverse, and driven. We believe that the best way to solve complicated dynamic problems is collaboratively and respectfully.
This role develops and scales large-scale machine learning training systems for multimodal robotics data, enabling the creation of high-performance autonomy models. By optimizing distributed training pipelines, neural network architectures, and data processing workflows, the position improves training efficiency, accelerates model iteration, and maximizes GPU utilization. The role collaborates closely with ML researchers and infrastructure teams, influencing the design, deployment, and performance of end-to-end autonomy models and the large-scale data pipelines that support them.
Responsibilities
  • Design and maintain training systems that can process and learn from petabyte-scale multimodal datasets (e.g., video and point cloud data). This includes ensuring data is efficiently loaded, distributed, and processed across large GPU clusters.
  • Identify and resolve bottlenecks in the training pipeline, including data loading, preprocessing, model computation, and inter-node communication, to maximize GPU utilization and reduce training time.
  • Work with the ML team to develop and refine neural network architectures suitable for autonomy tasks, particularly those handling high-dimensional and sequential sensor data.
  • Create and adjust loss functions and training strategies that help the model learn effectively from complex multimodal inputs and improve autonomy performance.
  • Configure, monitor, and maintain large-scale distributed training jobs across multiple machines and GPUs, ensuring stability, fault tolerance, and efficient resource usage.
  • Implement scalable systems to preprocess, transform, and augment large robotics datasets so that they are suitable for model training.
  • Work closely with ML scientists and other engineers to integrate new models, experiments, and training approaches into the production training pipeline.
  • Analyze training metrics, model outputs, and experiment logs to assess model performance and guide improvements in architecture, data usage, or training strategies.
  • Develop tools and workflows that allow teams to run experiments, track results, and iterate quickly on new model ideas or training approaches.

Qualifications
  • Master's or PhD in Computer Science, Robotics, Electrical Engineering, Machine Learning, or a closely related technical discipline.
  • Minimum of 5 years of professional experience developing, training, and deploying machine learning models in production environments.
  • Hands-on experience training machine learning models across multiple GPUs or compute nodes, including familiarity with distributed training frameworks and large dataset handling.
  • Strong programming skills in Python for implementing machine learning models, data pipelines, and training workflows.
  • Solid knowledge of core concepts such as neural networks, optimization algorithms, loss functions, model evaluation, and training methodologies.

What Makes You Stand out
  • Experience identifying and resolving training bottlenecks related to compute utilization, memory usage, and data throughput in machine learning systems.
  • Experience training machine learning models on robotics or autonomous driving datasets involving multimodal sensor inputs such as camera video, LiDAR point clouds, radar, or telemetry data.
  • Experience developing models that combine multiple data modalities (e.g., images, point clouds, and structured sensor data) into a unified learning system.
  • Peer-reviewed publications or significant research contributions in machine learning, robotics, or related areas.

*Please note: The listed base salary range applies to candidates based in the US. Compensation may vary depending on location, experience, and role alignment. We are open to qualified candidates working remotely in Canada
  • Canada - ALL: $177k - $215k CAD

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