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Machine Learning Engineer Python Jobs in Utah (NOW HIRING)

Tagup

Machine Learning Engineer

Salt Lake City, UT · On-site

We are seeking a Machine Learning Engineer to join our Salt Lake City team and help shape the next ... Required : • 4+ years of machine learning experience, with strong Python skills and proficiency ...

Leash Bio

Machine Learning Engineer

Salt Lake City, UT

$150K - $200K/yr

Machine Learning Engineer At Leash Biosciences, we are at the cutting edge of integrating machine learning with drug discovery. Our unique approach focuses on predicting molecular and protein ...

BILL

Senior Machine Learning Engineer

Draper, UT · On-site

$97.70K - $134.20K/yr

As a Senior Machine Learning Engineer , you'll play a pivotal role in designing, building, and ... Strong programming skills in Python and familiarity with ML frameworks such as TensorFlow , PyTorch ...

BILL

Senior Machine Learning Engineer

Draper, UT · On-site

$145.70K - $174.80K/yr

As a Senior Machine Learning Engineer , you'll play a pivotal role in designing, building, and ... Strong programming skills in Python and familiarity with ML frameworks such as TensorFlow , PyTorch ...

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Machine Learning Engineer Python information

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

To thrive as a Machine Learning Engineer Python, you need a solid background in computer science, statistics, and mathematics, along with proficiency in Python programming and machine learning concepts. Familiarity with frameworks such as TensorFlow, PyTorch, Scikit-learn, and experience with cloud platforms or MLOps tools are highly valued, as are certifications like Google Professional Machine Learning Engineer. Strong problem-solving abilities, communication skills, and a collaborative mindset help set you apart in this field. These skills enable engineers to design, implement, and deploy effective machine learning solutions that address real-world challenges in dynamic, team-oriented environments.

What are some common challenges faced by Machine Learning Engineers working with Python, and how can they be addressed?

Machine Learning Engineers using Python often encounter challenges such as managing large datasets, ensuring efficient model deployment, and maintaining reproducibility of experiments. Handling data pipelines and model versioning can be complex, especially as projects scale. To address these issues, engineers typically use tools like Pandas and Dask for data handling, Docker for containerization, and MLflow or DVC for tracking experiments and models. Collaborating closely with data engineers, software developers, and product teams is also essential to streamline workflows and ensure models are production-ready.

What is a Machine Learning Engineer Python?

A Machine Learning Engineer Python is a professional who uses the Python programming language to design, build, and deploy machine learning models and systems. They work with large datasets, develop algorithms, and use Python libraries such as TensorFlow, scikit-learn, and PyTorch to solve complex problems. Their responsibilities also include preprocessing data, training models, evaluating performance, and integrating solutions into production environments. Machine Learning Engineers often collaborate with data scientists, software engineers, and business stakeholders to create scalable and efficient machine learning applications.

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

AspectMachine Learning Engineer PythonData Scientist
Required CredentialsBachelor's/Master's in CS, Data Science, or related; Python skills; ML certificationsBachelor's/Master's in Statistics, CS, or related; Python/R skills; Data analysis certifications
Work EnvironmentDevelops scalable ML models, deploys algorithms, collaborates with engineering teamsAnalyzes data, builds models, interprets results, communicates insights
Employer & Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, marketing, research institutions

While both roles require Python proficiency and data skills, Machine Learning Engineers focus on building and deploying scalable ML models, whereas Data Scientists analyze data and generate insights. The roles often overlap but differ in their primary focus and responsibilities.

What are popular job titles related to Machine Learning Engineer Python jobs in Utah? For Machine Learning Engineer Python jobs in Utah, the most frequently searched job titles are:
What job categories do people searching Machine Learning Engineer Python jobs in Utah look for? The top searched job categories for Machine Learning Engineer Python jobs in Utah are:
What cities in Utah are hiring for Machine Learning Engineer Python jobs? Cities in Utah with the most Machine Learning Engineer Python job openings:
Machine Learning Engineer Python jobs near you
Infographic showing various Machine Learning Engineer Python job openings in Utah as of May 2026, with employment types broken down into 47% Full Time, 51% Part Time, and 2% Contract. Highlights an 94% Physical, 1% Hybrid, and 5% Remote job distribution.
Machine Learning Engineer

Machine Learning Engineer

Tagup

Salt Lake City, UT • On-site

Full-time

Posted 16 days ago

Job description

Job Summary:
Tagup is a defense technology company founded at MIT that is delivering logistics decision advantage with next-generation AI. We are seeking a Machine Learning Engineer to join our Salt Lake City team and help shape the next generation of AI-driven defense and aviation systems, focusing on designing, deploying, and scaling AI solutions for mission-critical operations.
Responsibilities:
• Develop, train, and optimize ML models for large-scale applications.
• Build pipelines for data ingestion and model deployment.
• Work with engineers and subject-matter experts to refine solutions.
• Conduct testing and validation to ensure reliability.
• Co-author technical reports on data analysis and model performance.
• Continuously improve ML infrastructure and workflows.
• Collaborate with customers to identify new data sources and the industrial processes they will support; some customer travel may be required.
Qualifications:
Required:
• 4+ years of machine learning experience, with strong Python skills and proficiency in frameworks such as PyTorch or TensorFlow.
• Proven ability to deploy ML models into production and work with large, complex datasets.
• Hands-on experience with MLOps tools and practices, including Kubernetes, MLflow, and CI/CD pipelines.
• Experience building and managing cloud infrastructure as code (AWS, Azure, or GCP) with tools such as Terraform or Ansible.
• Familiarity with datastores (MySQL, Postgres, or MongoDB) and prior exposure to aviation, defense, or other safety-critical environments is a plus.
Company:
Tagup provides asset management decision support, lowering the cost of in-service failures, business interruption, and equipment breakdown. Founded in 2015, the company is headquartered in Somerville, USA, with a team of 11-50 employees. The company is currently Early Stage.

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