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Senior Machine Learning Software Engineer Jobs in Layton, UT

Pwc

AI Engineer

Salt Lake City, UT · On-site

$50K - $112K/yr

... engineering to build and deploy ... software and platform systems that create Artificial Intelligence and Machine Learning-based ...

Mastercard, Inc.

Senior Software Engineer

Salt Lake City, UT · On-site

$118K - $156K/yr

Title and Summary Senior Software Engineer Who is Mastercard? Mastercard is a global technology company in the payments industry. Our mission is to connect and power an inclusive, digital economy ...

Draper

Senior Software Engineer

Clearfield, UT · On-site

$115K - $151K/yr

The Software Engineer (SMTS) works on mission-oriented projects, developing functional, scalable software solutions in an Agile environment. Responsibilities include designing algorithms, developing ...

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All JobsMachine Learning Software Engineer JobsSenior Machine Learning Software Engineer JobsSenior Machine Learning Software Engineer Jobs in Layton, UT

Senior Machine Learning Software Engineer information

See Layton, UT salary details

$68.6K

$130.2K

$174.4K

How much do senior machine learning software engineer jobs pay per year?

As of Aug 18, 2026, the average yearly pay for senior machine learning software engineer in Layton, UT is $130,190.00, according to ZipRecruiter salary data. Most workers in this role earn between $111,300.00 and $146,700.00 per year, depending on experience, location, and employer.

What is a senior machine learning software engineer?

A Senior Machine Learning Software Engineer is an experienced professional who designs, develops, and deploys machine learning models and systems to solve complex problems. They work closely with data scientists, engineers, and other stakeholders to build scalable and efficient solutions that leverage large data sets and advanced algorithms. Their responsibilities often include architecting ML pipelines, optimizing model performance, and mentoring junior team members. Typically, they have a strong background in computer science, programming, and applied mathematics, along with several years of hands-on experience in machine learning and software engineering.

What are some common challenges senior machine learning software engineers face when deploying models to production?

Senior Machine Learning Software Engineers often encounter challenges such as ensuring model scalability, maintaining performance under real-world data conditions, and integrating models seamlessly with existing systems. Handling data drift and monitoring model predictions for accuracy over time are also critical responsibilities. Collaboration with data engineers, DevOps, and product teams is essential to address these challenges and ensure robust, reliable deployments.

What are the key skills and qualifications needed to thrive as a senior machine learning software engineer, and why are they important?

A Senior Machine Learning Software Engineer requires deep expertise in machine learning algorithms, statistical analysis, and strong programming skills in languages like Python or Java, typically supported by a degree in computer science or a related field. Familiarity with frameworks such as TensorFlow, PyTorch, scikit-learn, as well as experience with cloud platforms and version control systems, is standard. Exceptional problem-solving, leadership, and communication skills help drive project success and mentor junior engineers. These competencies are crucial for designing scalable ML solutions, ensuring code quality, and effectively collaborating within cross-functional teams.

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

AspectSenior Machine Learning Software EngineerData Scientist
CredentialsBachelor's or Master's in CS, ML, or related; experience with ML frameworksBachelor's or Master's in Data Science, Statistics, or related; strong analytical skills
Work EnvironmentDevelops ML models, integrates algorithms into products, collaborates with engineering teamsAnalyzes data, builds statistical models, visualizes insights, collaborates with business teams
Industry UsageTech, finance, healthcare, e-commerceResearch, finance, marketing, healthcare

While both roles involve working with data and algorithms, Senior Machine Learning Software Engineers focus on developing and deploying scalable ML models within software systems, whereas Data Scientists primarily analyze data to generate insights and inform business decisions.

What job categories do people searching Senior Machine Learning Software Engineer jobs in Layton, UT look for?

The top searched job categories for Senior Machine Learning Software Engineer jobs in Layton, UT are:

What cities near Layton, UT are hiring for Senior Machine Learning Software Engineer jobs?

Cities near Layton, UT with the most Senior Machine Learning Software Engineer job openings:

Senior Machine Learning Software Engineer jobs near you
Infographic showing various Senior Machine Learning Software Engineer job openings in Layton, UT as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $130,190 per year, or $62.6 per hour.

Senior Associate, Software Engineer

L3HHCM20

Salt Lake City, UT • On-site

$117K - $154K/yr

Full-time

Posted 27 days ago

Job description

Job Title: Senior Associate, Software Engineer

Job Code: 41931

Job Location: Salt Lake City, UT

Job Schedule: 9/80 9/80 employees work 9 out of 14 days- totaling 80 hours worked- and have every other Friday off

 

Job Description:

 

The Electronic Warfare software engineering organization is seeking a Level 2 Software Engineer focused on system software development for embedded devices and communication systems. This role contributes across the full software development life cycle by working with cross-functional engineering teams to design, implement, integrate, test, and support software solutions in Linux, Windows, and embedded real-time operating system environments. The ideal candidate brings strong object-oriented software development skills, sound engineering judgment, and the ability to contribute effectively on technically complex programs.

 

Essential Functions:

 

  • Develop software for embedded devices and systems from requirements through production and support.
  • Work closely with cross-functional team members to develop operational performance requirements, interface software and hardware components, and collaborate on system design.
  • Support and participate in all phases of the software development life cycle, including requirements analysis, design, implementation, integration, and formal testing.
  • Contribute to software test plans, procedures, and other relevant technical documentation.
  • Participate in peer reviews, identify, track, and repair defects.
  • Collaborate with a cross-functional engineering team including systems, test, and program leadership.
  • Utilize a variety of software languages and tools on Windows, Linux, and embedded real-time operating systems.
  • Support software bids and proposal inputs in response to customer requests and government requests for proposal.
  • Travel is minimal.

 

Qualifications:

 

  • Bachelor's Degree and a minimum of 2 years of prior related experience. Graduate Degree or equivalent with 0 to 2 years of prior related experience. In lieu of a degree, minimum of 6 years of prior related experience.

 

Preferred Additional Skills:

 

  • Proficiency with C++.
  • Experience working with Department of Defense programs.
  • Experience with object-oriented software development using C++.
  • Experience with embedded real-time software development in Linux.
  • Experience with high-performance and multi-threaded programming.
  • Demonstrated depth of knowledge in programming languages, compilers, and application execution.
  • Ability to collaborate across engineering disciplines and contribute to complex technical efforts.
  • Ability to obtain and maintain a U.S. security clearance.
  • Experience with hands-on software development and troubleshooting on embedded targets.
  • Experience in embedded systems design.
  • Working knowledge of signal processing, control systems, electronic warfare, or networking.
  • Knowledge of protocols such as IP, UDP, TCP, and Protobufs.
  • Solid presentation and technical writing skills.

 

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