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Senior Tesla Machine Learning Engineer Jobs in Utah

They are seeking a highly skilled Machine Learning Engineer to manage large datasets, optimize cloud-based computing resources, and train advanced machine-learning models to contribute to new ...

Senior Machine Learning Engineer

Lehi, UT Β· On-site +1

$144K - $233K/yr

Following the launch of Forge , Entrata's proprietary AI platform, we are looking for a Senior Machine Learning Engineer to drive the next generation of our applied AI capabilities. You will play a ...

Senior Machine Learning Engineer

Lehi, UT Β· On-site +1

$144K - $233K/yr

Following the launch of Forge , Entrata's proprietary AI platform, we are looking for a Senior Machine Learning Engineer to drive the next generation of our applied AI capabilities. You will play a ...

Senior Machine Learning Engineer

Lehi, UT Β· On-site

$144K - $233K/yr

We are seeking a Senior Machine Learning Engineer to help build and scale Entrata's applied AI capabilities. This role will focus on adapting and fine-tuning foundation models for property management ...

The Opportunity Adobe is looking for Machine Learning Engineer interns to work on some of the most impactful AI systems in the industry - from generative AI features and intelligent agents to search ...

* Own model training and post-training pipelines end to end: SFT, RLHF, PPO, DPO, and reward model training in PyTorch * Build and maintain the infrastructure around RL training: rollout collection ...

* Own model training and post-training pipelines end to end: SFT, RLHF, PPO, DPO, and reward model training in PyTorch * Build and maintain the infrastructure around RL training: rollout collection ...

* Own model training and post-training pipelines end to end: SFT, RLHF, PPO, DPO, and reward model training in PyTorch * Build and maintain the infrastructure around RL training: rollout collection ...

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

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

Machine Learning Engineer

Salt Lake City, UT β€’ On-site

Full-time

Re-posted 9 days ago


Job description

Job Summary:
Leash Biosciences is at the forefront of integrating machine learning with drug discovery, aiming to revolutionize medicinal chemistry. They are seeking a highly skilled Machine Learning Engineer to manage large datasets, optimize cloud-based computing resources, and train advanced machine-learning models to contribute to new therapies for devastating diseases.
Responsibilities:
β€’ Manage and optimize data processing workflows for large-scale datasets, with an approach akin to language data handling.
β€’ Scale and maintain machine learning model training processes, with a focus on cloud environments (primarily Google Cloud, with flexibility to other platforms).
β€’ Collaborate closely with ML researchers, data scientists, and lab automation teams to ensure seamless integration of lab data and ML model training.
β€’ Innovate and iterate on our existing technology stack, taking the initiative to solve problems and improve our ML operations.
β€’ Act as a self-sufficient project manager, overseeing your projects from conception to completion.
Qualifications:
Required:
β€’ Strong experience in machine learning engineering, including data handling, model training, and scaling in cloud environments.
β€’ Comfortable building ML infrastructure
β€’ Experience working with large amounts of text data, NLP, or training LLMs
β€’ Demonstrated capability to make informed decisions, take ownership of solutions, and drive projects forward in a startup environment.
β€’ Excellent collaboration skills, with the ability to work effectively with cross-functional teams.
Preferred:
β€’ Familiarity with common MLops tooling (e.g., Dagster, Prefect, Airflow, Docker, MLflow, Kubeflow, W&B, Ray, etc.)
β€’ Ability to manage own compute cluster
β€’ Ability to maximize GPU utilization and keep cluster busy 24/7
β€’ Ability to analyze model results and kick off new experiments in response
β€’ Experience with BERT or similar language models in PyTorch.
β€’ Experience or interest in biology, chemistry, or related fields is a plus.
Company:
Leash Bio uses AI and machine learning to innovate drug design and medicinal chemistry. Founded in 2021, the company is headquartered in Salt Lake City, USA, with a team of 2-10 employees. The company is currently Early Stage.