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Phd Machine Learning Jobs in Utah (NOW HIRING)

Sr. Metallurgical Process Engineer

Moab, UT ยท On-site

$104K - $135K/yr

... machine learning teams * Ensure safe operations by supporting EHS, hazard assessments, risk management, and management of change processes What You'll Bring * B.S., M.S., or PhD in Chemical ...

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Phd Machine Learning information

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$12

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How much do phd machine learning jobs pay per hour?

As of Jul 15, 2026, the average hourly pay for phd machine learning in Utah is $20.78, according to ZipRecruiter salary data. Most workers in this role earn between $17.93 and $23.17 per hour, depending on experience, location, and employer.

What is a PhD in Machine Learning?

A PhD in Machine Learning is an advanced doctoral degree focused on developing new algorithms, theories, and applications in the field of machine learning. Graduates typically conduct original research, contribute to academic publications, and often specialize in areas like deep learning, reinforcement learning, or probabilistic modeling. This degree prepares individuals for careers in academia, industry research labs, or leadership roles in tech companies. The program usually involves coursework, comprehensive exams, and the completion of a dissertation based on novel research.

What are the key skills and qualifications needed to thrive as a PhD-level Machine Learning professional, and why are they important?

To thrive as a PhD-level Machine Learning professional, you need deep expertise in mathematics, statistics, computer science, and advanced machine learning algorithms, typically supported by a doctoral degree. Proficiency with programming languages like Python or R, machine learning frameworks such as TensorFlow or PyTorch, and experience with large-scale data systems are essential. Strong problem-solving skills, critical thinking, and effective communication set outstanding candidates apart by enabling them to tackle complex research challenges and collaborate across teams. These skills and qualities are crucial for driving innovation, publishing research, and developing impactful machine learning solutions.

What are some common challenges faced by PhD-level professionals in machine learning when transitioning from academia to industry roles?

PhD graduates in machine learning often encounter challenges such as adapting to faster-paced project timelines, aligning research with business objectives, and collaborating in multidisciplinary teams. Unlike academia, where projects can be exploratory and long-term, industry roles usually require actionable results within shorter deadlines. Additionally, communicating complex technical ideas to non-technical stakeholders and prioritizing practical solutions over theoretical novelty are key adjustments. However, these challenges also present opportunities for professional growth and broader impact.

What is the difference between Phd Machine Learning vs Data Scientist?

AspectPhd Machine LearningData Scientist
Required CredentialsPhD in Computer Science, AI, or related fieldBachelor's or Master's in Data Science, Statistics, or related field
Work EnvironmentResearch labs, academia, R&D departmentsBusiness, tech companies, analytics teams
Industry UsageResearch-focused roles, advanced algorithm developmentData analysis, model building, business insights
Common Search/ComparisonYesYes

While both roles involve working with data and algorithms, a Phd Machine Learning typically focuses on research, developing new models, and theoretical work, often in academic or R&D settings. A Data Scientist applies these techniques to solve practical business problems, analyze data, and generate insights in industry environments.

What cities in Utah are hiring for Phd Machine Learning jobs? Cities in Utah with the most Phd Machine Learning job openings:

Senior Software Engineer, Metrics and Evaluation - Autonomous Vehicles

NVIDIA AI

Santa Clara, UT โ€ข On-site

$109K - $144K/yr

Full-time

Posted 12 days ago


Job description

Job Summary:
NVIDIA AI is developing groundbreaking solutions in technology areas such as Artificial Intelligence and Autonomous Vehicles. They are seeking a Senior Software Engineer to join their Planning and Control team, focusing on metrics and evaluation to enable rapid algorithm development.
Responsibilities:
โ€ข Define and develop metrics that enable rapid debugging, testing, and evaluation of our Autonomous Vehicle software.
โ€ข Build compelling, data driven evaluation products by combining on-road driving analysis, large scale simulation, models, metrics and dashboards.
โ€ข Collaborate with machine learning engineers, infrastructure engineers and roboticists to develop novel solutions to open-ended problems
โ€ข Work with the Planning & Control team to develop and drive software testing strategies
Qualifications:
Required:
โ€ข MS, or PhD or equivalent experience in data science, electrical, mechanical, aerospace engineering, physics, computer science or similar fields
โ€ข 5+ years experience working in software engineering, data science, and/or experiment design roles
โ€ข Highly proficient in Python and associated libraries (Pandas, Numpy, Scipy, Matplotlib)
โ€ข Familiarity programming with GIT in Linux (Ubuntu) or another Unix based system
โ€ข Ability and enthusiasm to ramp up quickly on new technical domains
โ€ข Ability to multitask and prioritize in a fast paced environment
โ€ข Excellent organizational and interpersonal skills
Preferred:
โ€ข Experience developing on-board planning algorithms
โ€ข Developed metrics for autonomous vehicle robotics systems
โ€ข Experience with evaluating precision and recall of performance metrics
โ€ข Familiarity with C++
โ€ข Experience with working in a large monorepo and with Bazel as well as prior knowledge about vehicle simulation, path planning, vehicle control, Drive-by-Wire systems, and self-driving technologies.
Company:
Explore the latest breakthroughs made possible with AI. Founded in , the company is headquartered in Santa Clara, CA, US, , with a team of 10001+ employees. The company is currently Late Stage.