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Machine Learning Engineer Ts Sci Jobs in Utah (NOW HIRING)

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 ...

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 ...

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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Machine Learning Engineer Ts Sci information

What are Machine Learning Engineer TS/SCI positions?

Machine Learning Engineer TS/SCI positions are specialized roles where engineers design, develop, and implement machine learning models and systems, often for government or defense projects that require a Top Secret/Sensitive Compartmented Information (TS/SCI) security clearance. These professionals work on advanced AI algorithms, data processing, and secure software, ensuring that sensitive information is protected throughout the process. They collaborate with data scientists, software developers, and security experts to solve complex problems using data-driven approaches while adhering to strict security protocols.

What are the key skills and qualifications needed to thrive as a Machine Learning Engineer with TS/SCI clearance, and why are they important?

To thrive as a Machine Learning Engineer with TS/SCI clearance, you need strong skills in machine learning algorithms, programming (Python, R), data analysis, and a relevant degree in computer science or a related field, along with active TS/SCI security clearance. Familiarity with frameworks like TensorFlow or PyTorch, experience with cloud platforms (AWS, Azure), and knowledge of secure data handling are commonly required. Excellent problem-solving, teamwork, and clear communication are vital soft skills for collaborating on complex, sensitive projects. These skills ensure effective development of secure, high-impact AI solutions in environments where data protection and analytical precision are critical.

What are some common challenges faced by Machine Learning Engineers with TS/SCI clearance in day-to-day work?

Machine Learning Engineers with TS/SCI clearance often encounter unique challenges, such as working with highly sensitive data in secure environments, which can limit access to certain tools or cloud resources. Collaboration is often restricted to cleared team members, and sharing findings externally is not permitted. Additionally, projects may have ambiguous requirements due to their classified nature, requiring strong problem-solving skills and adaptability. However, these roles offer the chance to work on impactful projects with significant national security implications, providing both technical and professional growth.

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

AspectMachine Learning Engineer Ts SciData Scientist
Required CredentialsBachelor's or Master's in CS, Data Science, or related fields; certifications in ML or AIBachelor's or Master's in Statistics, Data Science, or related fields; certifications in data analysis or visualization
Work EnvironmentDevelops and deploys ML models, often in production environmentsAnalyzes data, builds models, and provides insights for decision-making
Employer & Industry UsageTech companies, AI firms, R&D departmentsFinance, healthcare, marketing, and tech sectors

While both roles require strong analytical skills and knowledge of machine learning, Machine Learning Engineer Ts Sci focuses on developing and deploying scalable ML models, whereas Data Scientists primarily analyze data to generate insights. The roles often overlap but differ in their core responsibilities and work environments.

What are popular job titles related to Machine Learning Engineer Ts Sci jobs in Utah? For Machine Learning Engineer Ts Sci jobs in Utah, the most frequently searched job titles are:
What cities in Utah are hiring for Machine Learning Engineer Ts Sci jobs? Cities in Utah with the most Machine Learning Engineer Ts Sci job openings:
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

Re-posted 9 days 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

158th of 882 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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