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Internship Deep Reinforcement Learning Jobs in Utah

Diversify Pathways Internship

Sandy, UT

$14.25 - $19/hr

... deep, hands-on understanding of the wealth management industry. This immersive program allows ... Hands-on, real-world work Understanding and applying SOPs and processes Project-based learning tied ...

Diversify Pathways Internship

Sandy, UT · On-site

$14.25 - $19/hr

... deep, hands-on understanding of the wealth management industry. This immersive program allows ... learning tied to firm growth and scalability • Mentorship and regular feedback

BCABA Tutor

Logan, UT · Remote

$18 - $40/hr

About the Job The Varsity Tutors Live Learning Platform has thousands of students looking for ... Deep knowledge of BCABA examination content covering basic behavior-analytic skills, philosophical ...

BCABA Tutor

Provo, UT · Remote

$18 - $40/hr

About the Job The Varsity Tutors Live Learning Platform has thousands of students looking for ... Deep knowledge of BCABA examination content covering basic behavior-analytic skills, philosophical ...

BCABA Tutor

Spanish Fork, UT · Remote

$18 - $40/hr

About the Job The Varsity Tutors Live Learning Platform has thousands of students looking for ... Deep knowledge of BCABA examination content covering basic behavior-analytic skills, philosophical ...

BCABA Tutor

Cedar City, UT · Remote

$18 - $40/hr

About the Job The Varsity Tutors Live Learning Platform has thousands of students looking for ... Deep knowledge of BCABA examination content covering basic behavior-analytic skills, philosophical ...

Preschool Teacher

Washington, UT · On-site

$13.50 - $18.25/hr

Intentionally develop our teachers to cultivate a nurturing learning environment where our children ... reinforcement, and by following our core values. Our company operates under the following core ...

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Infant Teacher

Washington, UT · On-site

$13 - $16.25/hr

Intentionally develop our teachers to cultivate a nurturing learning environment where our children ... reinforcement, and by following our core values. Our company operates under the following core ...

Infant Teacher

Ogden, UT · On-site

$14 - $17.50/hr

Intentionally develop our teachers to cultivate a nurturing learning environment where our children ... reinforcement, and by following our core values. Our company operates under the following core ...

Infant Teacher

Washington, UT · On-site

$13 - $16.25/hr

Intentionally develop our teachers to cultivate a nurturing learning environment where our children ... reinforcement, and by following our core values. Our company operates under the following core ...

Infant Teacher

Ogden, UT · On-site

$14 - $17.50/hr

Intentionally develop our teachers to cultivate a nurturing learning environment where our children ... reinforcement, and by following our core values. Our company operates under the following core ...

Preschool Teacher

Ogden, UT · On-site

$14.75 - $19.50/hr

Intentionally develop our teachers to cultivate a nurturing learning environment where our children ... reinforcement, and by following our core values. Our company operates under the following core ...

3's Teacher

Washington, UT

$13.50 - $18.25/hr

Intentionally develop our teachers to cultivate a nurturing learning environment where our children ... reinforcement, and by following our core values. Our company operates under the following core ...

Infant Teacher

Ogden, UT · On-site

$14 - $17.50/hr

Intentionally develop our teachers to cultivate a nurturing learning environment where our children ... reinforcement, and by following our core values. Our company operates under the following core ...

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Internship Deep Reinforcement Learning information

What types of projects or tasks can I expect to work on during a Deep Reinforcement Learning internship?

As a Deep Reinforcement Learning (DRL) intern, you'll typically work on projects involving the development, implementation, and evaluation of reinforcement learning algorithms. This might include tasks like training agents in simulated environments, tuning hyperparameters, analyzing performance metrics, and collaborating with team members to integrate DRL solutions into larger systems. You'll also likely spend time reading recent research papers, experimenting with frameworks such as TensorFlow or PyTorch, and presenting your findings to the research team. Collaboration with mentors and other interns is common, and you'll gain hands-on experience that prepares you for more advanced roles in AI research or engineering.

What is an internship in Deep Reinforcement Learning?

An internship in Deep Reinforcement Learning (DRL) is a temporary, hands-on position where interns learn and apply state-of-the-art machine learning algorithms that enable computers to learn decision-making tasks through trial and error. Interns typically work on projects involving neural networks, reward systems, and environments like games or simulations. These internships provide valuable experience with frameworks such as TensorFlow or PyTorch, and exposure to current research in artificial intelligence. The experience helps students or recent graduates build technical skills and prepare for careers in AI research or industry.

What are the key skills and qualifications needed to thrive as an Intern in Deep Reinforcement Learning, and why are they important?

To thrive as an Intern in Deep Reinforcement Learning, you need a solid background in mathematics (especially linear algebra, probability, and calculus), programming (Python), and foundational knowledge in machine learning principles, usually supported by ongoing or completed coursework in computer science or related fields. Familiarity with frameworks and tools such as TensorFlow, PyTorch, OpenAI Gym, and experience using version control systems like Git are typically required. Analytical thinking, curiosity, and effective communication are essential soft skills for collaborating on research problems and sharing complex findings. These skills and qualities are crucial for contributing to innovative projects and successfully navigating the challenges of cutting-edge AI research.

What is the difference between Internship Deep Reinforcement Learning vs Data Science Intern?

AspectInternship Deep Reinforcement LearningData Science Intern
Required SkillsMachine learning, programming (Python), reinforcement learning conceptsStatistics, data analysis, programming (Python/R), data visualization
Work EnvironmentResearch labs, AI companies, tech startupsBusiness analytics, tech firms, consulting agencies
Industry UsageAI research, robotics, autonomous systemsBusiness intelligence, marketing, finance

Internship Deep Reinforcement Learning focuses on developing algorithms that enable systems to learn through trial and error, often in AI research or robotics. Data Science Internships involve analyzing data to extract insights and support decision-making. While both roles require programming skills, reinforcement learning emphasizes AI-specific techniques, whereas data science centers on statistical analysis and data visualization.

What are the most commonly searched types of Deep Reinforcement Learning jobs in Utah? The most popular types of Deep Reinforcement Learning jobs in Utah are:
What are popular job titles related to Internship Deep Reinforcement Learning jobs in Utah? For Internship Deep Reinforcement Learning jobs in Utah, the most frequently searched job titles are:
What cities in Utah are hiring for Internship Deep Reinforcement Learning jobs? Cities in Utah with the most Internship Deep Reinforcement Learning job openings:

TECH ADJUNCT (Artificial Intelligence)

Neumont College of Computer Science

Salt Lake City, UT

Full-time

Posted 17 days ago


Job description

As a Neumont University instructor you will develop leadership and mentoring skills that will enhance your career. It can be a very rewarding experience as you see students start to understand complex subjects and gain confidence in their abilities.

Neumont is looking to fill multiple adjunct faculty positions to teach (in-person) in the following area:

  • Artificial Intelligence

Neumont University is looking for tech individuals with in-industry experience to teach the following technologies:

Artificial Intelligence:

  • Ability to teach AI fundamentals to complete beginners in clear, accessible terms
  • Familiarity with low-code AI tools, including Microsoft Azure ML Studio

AI Data Modeling:

  • Proficiency in SQL/SQLite and relational database design (entity-relationship modeling through normalization)
  • Experience with dimensional modeling / data warehousing (star schemas, OLTP vs. OLAP)
  • Understanding of how data modeling supports ML pipelines (feature stores, vector stores/embeddings, train/serve skew)
  • Ability to teach query optimization, including indexes and reading query execution plans
  • Strong working proficiency in Python, sufficient to review and debug student code live in class

Machine Learning Foundations:

  • Comfort teaching and evaluating algorithmic complexity (Big-O: time and space)
  • Solid grounding in core ML concepts: supervised/unsupervised/reinforcement learning, overfitting, neural network fundamentals

Reinforcement Learning:

  • Solid theoretical grounding in reinforcement learning (MDPs, Bellman equations, dynamic programming)
  • Hands-on experience with Monte Carlo methods, TD learning/SARSA, Q-learning, policy gradients, and DQNs
  • Working knowledge of NumPy and PyTorch
  • Ability to teach on-policy vs. off-policy tradeoffs and deep-RL stability concepts (replay buffers, target networks)

QUALIFICATIONS:

  • Bachelor’s or higher degree in computer science or a related field AND 4 years of CS related experience (or 8 years of CS related experience without a CS degree)
  • Teaching experience preferred, but not required
  • Ability to work within the U.S. without company sponsorship

LOCATION: In-person, on campus

TIME COMMITMENT:

  • Courses begin October 5, 2026 and are 5 to 10 weeks long, depending on the course.
  • We make classes work around full-time work schedules as we offer AM and PM classes.
  • Adjuncts may spend up to 10 hours a week outside of class doing grading and familiarizing themselves with the curriculum. This time commitment lessens once they get the hang of teaching.

ADVANTAGES TO BEING A NEUMONT FACULTY MEMBER:

  • Improve the lives of students from across the nation through the power of education.
  • Opportunity to give back through educating the next generation of tech experts.
  • Experience the "light" turn on in your student's eyes as you teach and they experience true understanding.
  • Be a part of a computer science institution that focuses on creating software engineers that can DO, not just theorize.
  • Develop your teaching/mentoring skills.

Faculty at Neumont University are responsible for educating students in accordance with the Neumont teaching methodology, which focuses on active learning and engaging students in the learning environment. Faculty members are also responsible for grading and providing valuable feedback to students in a timely manner, mentoring students in groups or individually, evaluating curriculum, adapting coursework and materials as necessary to meet student learning needs, and other activities related to effective instruction.

RESPONSIBILITIES, INCLUDING BUT NOT LIMITED TO:

  • Implement best practices in teaching and project-based learning
  • Submit all new teaching materials to Neumont vault upon completion of each course
  • Work with supervisor to identify areas for personal development and course improvement
  • Utilize feedback from mid-quarter and end-of-quarter evaluations to improve teaching
  • Identify innovative teaching methods to solve curricular problems
  • Teach material defined in the course description and syllabus
  • Maintain and meet the listed student learning goals
  • Utilize the Neumont LMS to keep an updated syllabus, course materials, and grades
  • Provide a safe learning environment for students
  • Answer and deal respectfully with student complaints and problems
  • Use effective assessments that measure student learning
  • Provide timely and accurate feedback to students’ assignments, exams, projects, etc.

FAQ

I’ve never taught before, am I qualified to teach?

We hire industry professionals and help them learn how to be good teachers. Our project-based curriculum means fewer lectures and more hands-on practice. Instructors must have at least 4 years of industry experience and a bachelor’s degree in a tech related field. An additional 4 years of outstanding experience and contributions to the field may be substituted for a formal degree.

Do I have to develop the curriculum?

You will use curriculum that has been developed and refined by previous Neumont instructors. We expect that you will share your individual perspective and experiences with the students to supplement the formal curriculum.

Does Neumont offer online courses?

No. Our classes are in-person as it makes for a better teaching/learning experience.

What is the process to get started?

All instructors will go through a formal application process which includes a short teaching demonstration. We will verify your work experience and educational credentials.

NU is an equal opportunity employer and provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.

Neumont’s Annual Security & Fire Safety Report is available online at https://www.neumont.edu/campus-safety under the Student Life section. This report is required by federal law to comply with the Jeanne Clery Disclosure of Campus Security Policy and Campus Crime Statistics Act and contains policy statements and crime statistics for the school. The policy statements address the school’s policies, procedures and programs concerning safety and security. You may also request a paper copy from the Vice President, Student Affairs.