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Freelance Google Machine Learning Engineer Jobs in Utah

Bespoke Labs

Machine Learning Engineer

Logan, UT · On-site

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Bespoke Labs

Machine Learning Engineer

Ogden, UT

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Bespoke Labs

Machine Learning Engineer

Orem, UT · On-site

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Bespoke Labs

Machine Learning Engineer

Logan, UT

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Bespoke Labs

Machine Learning Engineer

Ogden, UT · On-site

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Bespoke Labs

Machine Learning Engineer

Orem, UT

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

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Freelance Google Machine Learning Engineer information

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

To thrive as a Freelance Google Machine Learning Engineer, you need a solid background in computer science, statistics, and machine learning, typically supported by a relevant degree and experience with real-world data projects. Familiarity with Google Cloud Platform (GCP), TensorFlow, and certifications like Google Professional Machine Learning Engineer are commonly required. Strong problem-solving abilities, self-motivation, and effective client communication distinguish top freelancers in this field. These skills and qualifications are crucial for delivering robust machine learning solutions tailored to client needs and efficiently navigating remote, project-based work.

What does a Freelance Google Machine Learning Engineer do?

A Freelance Google Machine Learning Engineer is a technical specialist who designs, develops, and deploys machine learning models using Google’s tools and platforms, such as TensorFlow and Google Cloud AI services. They work independently or with clients to solve data-driven problems, build predictive models, and automate processes using machine learning techniques. Their responsibilities may include data preprocessing, feature engineering, model training and evaluation, and integrating models into production systems. Freelancers often manage multiple projects and must stay updated on the latest ML advancements and Google technologies.

What are some common challenges freelance Google Machine Learning Engineers face when working with clients remotely?

Freelance Google Machine Learning Engineers often encounter challenges such as clearly defining project scopes, aligning on deliverables, and managing expectations, especially when working remotely. Communication can be more complex due to time zone differences and varying levels of technical understanding among clients. Staying updated with Google’s latest ML tools and ensuring secure, efficient data sharing are also important. Building strong documentation and regular progress updates can help foster trust and smooth collaboration.

What is the difference between Freelance Google Machine Learning Engineer vs Freelance Data Scientist?

AspectFreelance Google Machine Learning EngineerFreelance Data Scientist
CredentialsKnowledge of Google Cloud ML tools, programming skills in Python, TensorFlowStatistical expertise, programming in Python/R, data analysis skills
Work EnvironmentCloud platforms, AI/ML projects, collaboration with developersData analysis, reporting, model development, client communication
Industry UsageTech companies, AI startups, cloud service providersFinance, healthcare, marketing, research organizations

While both roles involve working with data and models, a Freelance Google Machine Learning Engineer specializes in deploying ML solutions on Google Cloud, focusing on AI/ML engineering tasks. A Freelance Data Scientist primarily analyzes data, builds statistical models, and provides insights. The roles overlap in skills but differ in focus and tools used.

What are the most commonly searched types of Google Machine Learning Engineer jobs in Utah? The most popular types of Google Machine Learning Engineer jobs in Utah are:
What are popular job titles related to Freelance Google Machine Learning Engineer jobs in Utah? For Freelance Google Machine Learning Engineer jobs in Utah, the most frequently searched job titles are:
What job categories do people searching Freelance Google Machine Learning Engineer jobs in Utah look for? The top searched job categories for Freelance Google Machine Learning Engineer jobs in Utah are:
What cities in Utah are hiring for Freelance Google Machine Learning Engineer jobs? Cities in Utah with the most Freelance Google Machine Learning Engineer job openings:
Freelance Google Machine Learning Engineer jobs near you
Senior Machine Learning Engineer

Senior Machine Learning Engineer

University of Utah Health

Salt Lake City, UT • On-site

$101K - $138K/yr

Full-time

Medical, Dental

Posted 18 hours ago

University Of Utah Health rating

7.7

Company rating: 7.7 out of 10

Based on 140 frontline employees who took The Breakroom Quiz

160th of 877 rated healthcare providers

Job description

Overview
As a patient-focused organization, University of Utah Health exists to enhance the health and well-being of people through patient care, research and education. Success in this mission requires a culture of collaboration, excellence, leadership, and respect. University of Utah Health seeks staff that are committed to the values of compassion, collaboration, innovation, responsibility, integrity, quality and trust that are integral to our mission. EO/AA
Senior Machine Learning Engineers leverage their engineering expertise to solve a variety of technical problems for some of the most challenging and impactful projects in healthcare informatics and machine learning. You will work on a specific project critical to our needs with the opportunity to switch teams and projects as you and our fast-paced business grow. We need machine learning engineers who are versatile, rigorous, display leadership qualities and are enthusiastic to take on new problems. You will design, develop, test, deploy, maintain and enhance machine learning and AI solutions.You will be part of the Innovation Office, a product factory inside the health system of the University of Utah.
Corporate Overview: University of Utah Health is an integrated academic healthcare system with five hospitals including a level 1 trauma center, eleven community health centers, over 1,600 providers, and a health plan serving over 200,000 members. University of Utah Health is nationally ranked and recognized for our academic research, quality standards and overall patient experience. In addition to our clinical delivery system, we have a School of Medicine, School of Dentistry, College of Nursing, College of Pharmacy, and College of Health providing education and training for over 1,250 providers annually. We have over 2 million patient visits annually and research grants exceeding $350 million. University of Utah Hospitals and Clinics represents our clinical operations for the larger health system.
Responsibilities
Essential Functions
  • Creating, managing, maintaining, and refactoring ML codebases, pipelines, and workflows for the innovation office.
  • Collaborating closely with research, medical, and engineering staff to design and implement ML approaches.
  • Implementing scalable ML methods and workflows for high-performance computing (HPC) resources, in close collaboration with research staff and technical staff.
  • Review code developed by other developers and provide feedback to ensure best practices (e.g., style guidelines, checking code in, accuracy, testability, and efficiency).
  • Troubleshooting data analysis issues, including implementation issues, hyper-parameter choices and modeling decision.
  • Assisting in preparation of manuscripts and dissemination of results in the appropriate venues.
  • Conducing tasks independently and communicate optimally to team members and stakeholders.
  • Developing deployable solutions for the health care system.
Knowledge / Skills / Abilities
  • Hands-on coding in C++, Python, PyTorch, or Tensorflow.
  • Foundational understanding of supervised and unsupervised learning, reinforcement learning, and machine learning.
  • Independently execute in the face of ambiguity
  • Leads identifications of dependencies and the development of design documents for a product, application, service, or platform.
  • Write efficient systems code and tests and able to debug distributed systems.
  • Work on-call to monitor systems/product/service for degradation, downtime or interruptions.
  • Innovative mindset with a keen eye for identifying opportunities for improvement.
  • Ability to thrive in a fast-paced, dynamic environment and simultaneously handle multiple projects.
  • Partner effectively with other engineers, product managers, and stakeholders.

Qualifications
Required
  • Bachelor's degree in a relevant field.
  • 5 years of experience in software engineering.

Qualifications (Preferred)
Preferred
  • Experience working in complex academic medical center environments.
  • Experience with large multimodal health datasets.
  • Experience with lifecycle management in a fast-paced software environment.
  • Experience in shipping products and scalable, reliable services.
  • Hands on experience with asynchronous programming and concurrency (threads, tasks, futures, async/await).
  • Experience with Azure Kubernetes Service (AKS), Amazon Elastic Kubernetes Service (EKS), and/or Google Kubernetes Engine (GKE) '
  • Experience in building database engines, query engines, indexing solutions (columnar, full-text, vector), at scale.
  • Experience with programming CUDA, AI systems at scale.
  • Experience with live site operations, Site Reliability Engineering (SRE) or production support roles.
  • Experience in networking, distributed systems, lower-level infrastructure.
  • Experience developing accessible technologies.
  • Proficiency in code and system health, diagnosis and resolution, and software test engineering.
  • Experience with AI agents.
Working Conditions and Physical Demands
Employee must be able to meet the following requirements with or without an accommodation.
  • This is a sedentary position that may exert up to 10 pounds and may lift, carry, push, pull or otherwise move objects. This position involves sitting most of the time and is not exposed to adverse environmental conditions.

Physical Requirements
Listening, Sitting, Speaking, Standing, Walking

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