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Freelance Google Machine Learning Engineer Jobs in Utah

AI Engineer

Salt Lake City, UT · On-site

$50K - $112K/yr

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

Certifications aligned to data engineering, machine learning, and cloud platforms, including AWS, Google Cloud, Microsoft Azure, Databricks, Snowflake, or related data and AI credentials - Building ...

Sr. Applied AI Engineer

Salt Lake City, UT · On-site

$101K - $138K/yr

AWS Certified Machine Learning Engineer - Associate or equivalent * Cloud AI infrastructure management using AWS services and Terraform * AI observability experience with OpenTelemetry, Langfuse, or ...

Sr. Applied AI Engineer

Salt Lake City, UT

$101K - $138K/yr

AWS Certified Machine Learning Engineer - Associate or equivalent * Cloud AI infrastructure management using AWS services and Terraform * AI observability experience with OpenTelemetry, Langfuse, or ...

AI Infrastructure Engineer IV

Lehi, UT · On-site

$100K - $132K/yr

... our AI and machine learning capabilities. You will ensure our compute, storage, and cloud ... Hands-on experience with cloud platforms such as AWS, Azure, or Google Cloud. * Proficiency with ...

AI Infrastructure Engineer IV

Mendon, UT · On-site

$93K - $122K/yr

... our AI and machine learning capabilities. You will ensure our compute, storage, and cloud ... Hands-on experience with cloud platforms such as AWS, Azure, or Google Cloud. * Proficiency with ...

Data Scientists

Salt Lake City, UT · On-site

$75K - $105K/yr

  • Retirement

Apply knowledge of statistics, machine learning, programming, data modeling, simulation, and advanced mathematics to recognize patterns, identify opportunities, pose business questions, and make ...

Apply knowledge of statistics, machine learning, programming, data modeling, simulation, and advanced mathematics to recognize patterns, identify opportunities, pose business questions, and make ...

AI Engineer

Saint George, UT · On-site

$50K - $90K/yr

About The Role As an AI Engineer, you will design, build, and deploy sophisticated AI solutions ... Collaborating closely with cross-functional teams, you will develop and optimize machine learning ...

About The Role As an AI Engineer, you will design, build, and deploy sophisticated AI solutions ... Collaborating closely with cross-functional teams, you will develop and optimize machine learning ...

Showing results 41-60

Freelance Google Machine Learning Engineer information

What are the key skills and qualifications needed to thrive as a freelance Google Machine Learning Engineer?

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 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:

Platform Engineer Machine Learning (Utah)

Waystar, Inc

Lehi, UT • On-site

$100 - $130/hr

Other

Medical, Retirement, PTO

Re-posted 5 days ago


Job description

Responsibilities
  • Develop and enhance the machine learning platform to manage the full model life cycle.
  • Build frameworks and tools to enable the data science team in developing and enhancing predictive models, and support scalable real‑time predictions in production.
  • Design and implement data‑engineering solutions for model training.
  • Expand NLP capabilities with advanced analysis techniques to improve text understanding.
  • Design and implement high‑performance, scalable services and applications.
  • Collaborate with team members to create integrated solutions and ensure timely delivery of quality software and documentation.
  • Understand and adhere to development standards for consistency across teams.
  • Perform in‑depth technical and performance analyses to troubleshoot production issues.
  • Monitor and maintain production systems for reliability and efficiency.
Minimum Requirements
  • Bachelor’s degree in Computer Science or a related field;Master’s degree preferred.
  • 7+ years of professional experience writing Python or Java code, with at least 3years building data platforms.
  • Expert proficiency with SQL and NLP.
  • Seasoned practitioner of engineering best practices such as CI/CD and automated testing.
  • Comfortable working in a Linux environment.
  • Passion for exploring, applying, and following the evolution of cutting‑edge technologies related to AI, machine learning, NLP, and large‑scale data processing.
  • Professional experience with MLOps, Docker, Kubernetes, relational databases (PostgreSQL preferred), Kafka, REST API design, and microservices application architectures.
  • Experience with public cloud solutions, such as AWS or GCP.
  • Proven track record of successful delivery of progressively complex technical projects.
  • Coaching and mentoring junior engineers.
  • Team‑player DNA with a positive, self‑starter attitude.
  • Attention to detail, highly organized, with an absolute focus on quality of work.
Preferred Requirements
  • Familiarity with ClearML, Triton, PyTorch, and TensorFlow.
  • Familiarity with statistics and the healthcare domain.
  • Proven expertise in successful large project/build management and execution.
Benefits
  • Competitive total rewards (base salary + bonus, if applicable).
  • Customizable benefits package (three medical plans with Health Savings Account company match).
  • Generous paid time off: 3weeks + 13 paid holidays for non‑exempt team members; flexible time off for exempt team members + 13 paid holidays.
  • Paid parental leave (including maternity and paternity leave).
  • Education assistance opportunities and free LinkedIn Learning access.
  • Free mental health and family planning programs, including adoption assistance and fertility support.
  • 401(k) program with company match.
  • Pet insurance.
  • Employee resource groups.
Equal Opportunity Statement

Waystar is proud to be an equal‑opportunity workplace. Qualified applicants will receive consideration for employment without regard to race, color, religion, age, sex, national origin, disability status, genetics, marital status, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local laws. This applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, and training.

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