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Contract Audio Machine Learning Jobs in Tooele, UT

Pluralsight, LLC

SLED Account Executive

Draper, UT · On-site

Experience managing a pipeline and closing SLED contracts, at the state or state agency level ... and machine learning. We offer highly curated content developed by vetted technology experts ...

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All JobsContract Audio Machine Learning JobsContract Audio Machine Learning Jobs in Tooele, UT

Contract Audio Machine Learning information

See Tooele, UT salary details

$28

$45

$92

How much do contract audio machine learning jobs pay per hour?

As of Aug 5, 2026, the average hourly pay for contract audio machine learning in Tooele, UT is $45.94, according to ZipRecruiter salary data. Most workers in this role earn between $38.61 and $47.60 per hour, depending on experience, location, and employer.

What is the difference between Contract Audio Machine Learning vs Contract Data Scientist?

AspectContract Audio Machine LearningContract Data Scientist
Required CredentialsDegree in Computer Science, Data Science, or related field; experience with machine learning frameworksDegree in Data Science, Statistics, or related; strong programming skills
Work EnvironmentFocus on audio data, signal processing, and machine learning modelsBroader data analysis, statistical modeling, and data visualization
Industry UsageMedia, entertainment, speech recognition, audio analysisFinance, healthcare, marketing, and various industries requiring data insights

Contract Audio Machine Learning specialists focus on developing models specifically for audio data, while Contract Data Scientists handle a wider range of data types and analysis tasks. Both roles require strong technical skills, but their focus areas and industry applications differ.

Contract Audio Machine Learning jobs near you

Internship - Machine Learning Engineer

Smule

Salt Lake City, UT • Remote

Other

Re-posted 3 days ago

Job description

Salary:

Smule has been on a mission to bring the world together through music since 2008. Music is much more than listening it's about creating, sharing, discovering, participating, and connecting with people. With dozens of millions of monthly active users creating over 20 million songs every day, Smule is connecting people all over the world through the joy of making music and transforming the music landscape from one of passive listening to collaborative creative expression and active engagement.


About the Role:

We are looking for a Machine Learning Engineer to own the end-to-end lifecycle of ML models in production at Smule, from training and optimization through deployment, monitoring, and iteration. You will work closely with research scientists to bring models off the bench and into scalable, reliable systems that serve millions of users. The ideal candidate is a strong engineer first, with deep practical knowledge of ML systems, a passion for reliability, and an eye for performance.


We strongly encourage candidates with non-traditional backgrounds to apply. If your path into ML engineering came through backend systems, DevOps, audio software, data engineering, or another field, we want to hear from you.


What You'll Be Doing:

  • Design, build, and maintain production ML pipelines encompassing data ingestion, feature engineering, model training, evaluation, and deployment.
  • Optimize models for production constraints including latency, throughput, memory footprint, and cost, using techniques such as quantization, distillation, pruning, and efficient serving architectures.
  • Implement robust monitoring, alerting, and observability for deployed models, covering data drift, prediction quality, and system health.
  • Collaborate with research scientists to integrate new model architectures and training techniques into production systems with minimal friction.
  • Build and improve CI/CD pipelines for ML, including automated testing, validation gates, and staged rollouts.
  • Manage compute infrastructure and costs, making informed tradeoffs between performance, reliability, and budget.


What We're Looking For:

  • Degree (B.S., M.S., or Ph.D.) in Computer Science, Software Engineering, Electrical Engineering, or a related technical discipline, or currently pursuing one.
  • Strong proficiency in Python and experience with deep learning serving (TorchServe, Triton, vLLM, or equivalent).
  • Solid understanding of systems engineering: networking, storage, containerization, orchestration, and monitoring.
  • Ability to reason about tradeoffs between latency, throughput, cost, and model quality.


Bonus Points For:

  • Experience serving large language models or other generative models at scale.
  • Familiarity with audio/music processing pipelines and real-time inference constraints.
  • Experience with Bayesian optimization, bandit algorithms, or adaptive experimentation platforms.
  • Contributions to open-source ML infrastructure projects.


Smule is an Equal Opportunity Employer and considers all qualified applicants without regard to race, color, religion, sex, gender identity or expression, sexual orientation, national origin, ancestry, age, disability, medical condition, genetic information, marital status, military or veteran status, or any other protected characteristic under federal, state, or local law.


We are committed to creating an inclusive environment for all employees and applicants. If you require a reasonable accommodation during the application or interview process, please let us know.