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Urgently Hiring Apple Machine Learning Engineer Jobs in Utah

Senior Machine Learning Engineer

Lehi, UT · On-site +1

$144K - $233K/yr

We are seeking a Senior Machine Learning Engineer to help build and scale Entrata's applied AI ... Final hiring decisions are ultimately made by humans. If you would like more information about how ...

Senior Machine Learning Engineer

Lehi, UT · On-site +1

$144K - $233K/yr

We are seeking a Senior Machine Learning Engineer to help build and scale Entrata's applied AI ... Final hiring decisions are ultimately made by humans. If you would like more information about how ...

Senior Machine Learning Engineer

Sandy, UT · Hybrid

$99K - $136K/yr

As Senior Machine Learning Engineer, you will own the evaluation and optimization of speech-oriented AI models - covering real-time transcription and speech-to-speech systems across dozens of ...

Senior Machine Learning Engineer

Sandy, UT · On-site

$113K - $150K/yr

As Senior Machine Learning Engineer, you will own the evaluation and optimization of speech-oriented AI models - covering real-time transcription and speech-to-speech systems across dozens of ...

Senior Machine Learning Engineer

Lehi, UT · On-site

$144K - $233K/yr

We're looking for a Senior AI and Machine Learning Engineer to help design, build, and optimize our ... Final hiring decisions are ultimately made by humans. If you would like more information about how ...

Senior Engineer - Machine Learning

Midvale, UT · Hybrid

$98K - $135K/yr

As a Senior Engineer, Machine Learning at Berkadia, you'll be at the forefront of applying cutting-edge machine learning and generative AI to redefine how the commercial real estate industry operates.

Senior Engineer - Machine Learning

Midvale, UT · On-site

$98K - $135K/yr

As a Senior Engineer, Machine Learning at Berkadia, you'll be at the forefront of applying cutting-edge machine learning and generative AI to redefine how the commercial real estate industry operates.

As a Senior Engineer, Machine Learning at Berkadia, you'll be at the forefront of applying cutting-edge machine learning and generative AI to redefine how the commercial real estate industry operates.

Machine Learning Tutor

Logan, UT · 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 ...

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Urgently Hiring Apple Machine Learning Engineer information

What does an Apple machine learning engineer do?

An Apple Machine Learning Engineer designs, builds, and deploys machine learning models and algorithms that enhance Apple’s products and services. They collaborate with cross-functional teams to develop innovative solutions, optimize existing machine learning systems, and ensure models run efficiently on Apple hardware and software platforms. Their work includes data analysis, model training, and performance tuning, often focusing on privacy, scalability, and user experience.

What are the key skills and qualifications needed to thrive as an Apple machine learning engineer?

To thrive as an Apple Machine Learning Engineer, you need a strong background in computer science, mathematics, and machine learning principles, often supported by a relevant degree and experience with model development. Proficiency with Python, TensorFlow or PyTorch, and familiarity with macOS/iOS development tools like Core ML are typically required. Strong problem-solving, collaboration, and communication skills help engineers to innovate and work effectively across multidisciplinary teams. These competencies are crucial for driving impactful AI solutions that enhance Apple’s products and user experiences.

What are common collaboration practices for Apple machine learning engineers working on product teams?

Apple Machine Learning Engineers typically collaborate closely with cross-functional teams, including software engineers, product managers, and data scientists. Collaboration often involves regular meetings to align on project goals, integrating machine learning models into production systems, and jointly troubleshooting issues that arise during development. Engineers are encouraged to share findings and best practices, leveraging Apple's internal tools and documentation to ensure that models are robust, scalable, and meet Apple's privacy standards. The work environment emphasizes innovation, open communication, and a high standard of quality, which means collaboration is both structured and dynamic.

What is the difference between Urgently Hiring Apple Machine Learning Engineer vs Apple Data Scientist?

AspectApple Machine Learning EngineerApple Data Scientist
Required CredentialsBachelor's or higher in CS, ML, or related; experience with ML frameworksBachelor's or higher in CS, Statistics, or related; strong analytical skills
Work EnvironmentDeveloping ML models, deploying AI solutions, coding in Python, TensorFlowAnalyzing data, creating reports, statistical modeling, data visualization
Employer & Industry UsageTech companies, AI/ML product teams, innovation labsTech companies, analytics teams, product development

While both roles involve working with data and algorithms at Apple, the Machine Learning Engineer focuses on building and deploying ML models, whereas the Data Scientist emphasizes analyzing data and deriving insights. The roles overlap but differ mainly in technical focus and daily tasks.

What are the most commonly searched types of Apple Machine Learning Engineer jobs in Utah?

The most popular types of Apple Machine Learning Engineer jobs in Utah are:

What cities in Utah are hiring for Urgently Hiring Apple Machine Learning Engineer jobs?

Cities in Utah with the most Urgently Hiring Apple Machine Learning Engineer job openings:

Machine Learning Engineer

Leash Bio

Salt Lake City, UT • On-site

Full-time

Re-posted 16 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:
• Manage and optimize data processing workflows for large-scale datasets, with an approach akin to language data handling.
• Scale and maintain machine learning model training processes, with a focus on cloud environments (primarily Google Cloud, with flexibility to other platforms).
• Collaborate closely with ML researchers, data scientists, and lab automation teams to ensure seamless integration of lab data and ML model training.
• Innovate and iterate on our existing technology stack, taking the initiative to solve problems and improve our ML operations.
• Act as a self-sufficient project manager, overseeing your projects from conception to completion.
Qualifications:
Required:
• Strong experience in machine learning engineering, including data handling, model training, and scaling in cloud environments.
• Comfortable building ML infrastructure
• Experience working with large amounts of text data, NLP, or training LLMs
• Demonstrated capability to make informed decisions, take ownership of solutions, and drive projects forward in a startup environment.
• Excellent collaboration skills, with the ability to work effectively with cross-functional teams.
Preferred:
• Familiarity with common MLops tooling (e.g., Dagster, Prefect, Airflow, Docker, MLflow, Kubeflow, W&B, Ray, etc.)
• Ability to manage own compute cluster
• Ability to maximize GPU utilization and keep cluster busy 24/7
• Ability to analyze model results and kick off new experiments in response
• Experience with BERT or similar language models in PyTorch.
• 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.