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Entry Level Machine Learning Engineer Jobs in Las Vegas, NV

Mechatronics Engineer

Henderson, NV · On-site

$85 - $125/hr

Programming and debugging embedded systems and control algorithms. * Analyzing system failures and ... Knowledge of the Internet of Things (IoT), Machine Learning (ML), and Artificial Intelligence (AI ...

Programming and debugging embedded systems and control algorithms. * Analyzing system failures and ... Knowledge of the Internet of Things (IoT), Machine Learning (ML), and Artificial Intelligence (AI ...

Machine Operator

Las Vegas, NV · On-site

$16.25 - $19.25/hr

The primary focus of this entry level position is to learn to maintain, troubleshoot, and repair ... Specific duties for this position include learning and then performing basic machine and ...

Risk Modeler I

Las Vegas, NV · On-site

$52.75 - $68.50/hr

The Model Development team challenges the status quo through their statistical and machine learning ... Bachelor's Degree in STEM (Science, Technology, Engineering, and Mathematics) or related field.

Risk Modeler I

Las Vegas, NV

$52.75 - $68.50/hr

The Model Development team challenges the status quo through their statistical and machine learning ... Bachelor's Degree in STEM (Science, Technology, Engineering, and Mathematics) or related field.

Risk Modeler I

Las Vegas, NV

$52.75 - $68.50/hr

The Model Development team challenges the status quo through their statistical and machine learning ... Bachelor's Degree in STEM (Science, Technology, Engineering, and Mathematics) or related field.

Senior Optical Engineer

Las Vegas, NV · On-site

$95K - $131K/yr

Senior Optical Engineer for Space Domain Awareness Projects Location: Las Vegas, NV EO Solutions ... and machine learning (ML). Our expertise enables us to quickly prototype and implement ...

Deep knowledge of statistical analysis, data wrangling, exploratory data analysis, machine learning, data visualization, SQL, Python or R programming, hypothesis testing, and communication of data ...

Data Science Tutor

Las Vegas, NV · Remote

$18 - $40/hr

Deep knowledge of statistical analysis, data wrangling, exploratory data analysis, machine learning, data visualization, SQL, Python or R programming, hypothesis testing, and communication of data ...

Data Science Tutor

Henderson, NV · Remote

$18 - $40/hr

Deep knowledge of statistical analysis, data wrangling, exploratory data analysis, machine learning, data visualization, SQL, Python or R programming, hypothesis testing, and communication of data ...

Staff Front End Engineer

Las Vegas, NV · On-site +1

$172K - $229K/yr

This role will directly contribute through the creation of critical web tooling and visualization that allows us to improve our feedback loops for machine learning (ML) engineers and improve the ...

Python Tutor

Las Vegas, NV · Remote

$18 - $40/hr

Emphasizes readable, maintainable code and connects Python to machine learning, web scraping, scientific computing, and DevOps applications. * Curriculum Awareness & Adaptive Instruction: Familiar ...

Python Tutor

Henderson, NV · Remote

$18 - $40/hr

Emphasizes readable, maintainable code and connects Python to machine learning, web scraping, scientific computing, and DevOps applications. * Curriculum Awareness & Adaptive Instruction: Familiar ...

Python Tutor

North Las Vegas, NV · Remote

$18 - $40/hr

Emphasizes readable, maintainable code and connects Python to machine learning, web scraping, scientific computing, and DevOps applications. * Curriculum Awareness & Adaptive Instruction: Familiar ...

CNC Programmer

Las Vegas, NV · On-site

$25 - $34/hr

Experience operating CNC milling and/or turning machines. * Entry-level to intermediate experience with CNC programming software. * Familiarity with G-code and common CAM or controller software.

Data Analyst

Las Vegas, NV · On-site

$25 - $35/hr

... programming skills, with the ability to apply these tools for data processing, analysis, and ... machine learning techniques (e.g., classification, clustering, tree-based models) is a plus.

Showing results 21-40

Entry Level Machine Learning Engineer information

See Las Vegas, NV salary details

$28.8K

$66.7K

$113.4K

How much do entry level machine learning engineer jobs pay per year?

As of Aug 21, 2026, the average yearly pay for entry level machine learning engineer in Las Vegas, NV is $66,662.00, according to ZipRecruiter salary data. Most workers in this role earn between $49,500.00 and $75,400.00 per year, depending on experience, location, and employer.

What is an entry level machine learning engineer?

An Entry Level Machine Learning Engineer is responsible for developing, testing, and deploying machine learning models under the guidance of senior engineers. They work with datasets, implement algorithms, and optimize model performance. Their role often involves data preprocessing, feature engineering, and collaborating with data scientists and software engineers. Strong programming skills in Python, knowledge of ML frameworks like TensorFlow or PyTorch, and an understanding of statistics and algorithms are essential. This position serves as a foundation for building expertise in artificial intelligence and data-driven decision-making.

What are some typical projects or tasks an entry level machine learning engineer might work on?

As an Entry Level Machine Learning Engineer, you’ll often work on tasks such as data preprocessing, feature engineering, and assisting in training and evaluating models under the guidance of senior engineers or data scientists. You may help develop prototypes, automate data collection pipelines, and collaborate with software engineers to integrate machine learning solutions into products. Working in this role typically involves frequent collaboration in a team environment, participating in code reviews, and learning best practices for scalable model deployment. These foundational experiences are designed to build your technical expertise and set the stage for future growth within the field.

What are the key skills and qualifications needed to thrive as an entry level machine learning engineer?

To thrive as an Entry Level Machine Learning Engineer, you need a solid understanding of machine learning algorithms, programming languages like Python, and a degree in computer science, engineering, or a related field. Familiarity with tools such as TensorFlow, PyTorch, scikit-learn, and version control systems like Git is highly valuable, and completing online courses or certifications can further demonstrate your skills. Strong analytical thinking, attention to detail, and effective communication are important soft skills in this role. These abilities are essential because they enable you to build accurate models, work collaboratively with teams, and communicate insights to stakeholders.

What are the most commonly searched types of Machine Learning Engineer jobs in Las Vegas, NV?

The most popular types of Machine Learning Engineer jobs in Las Vegas, NV are:

What are popular job titles related to Entry Level Machine Learning Engineer jobs in Las Vegas, NV?

For Entry Level Machine Learning Engineer jobs in Las Vegas, NV, the most frequently searched job titles are:

What job categories do people searching Entry Level Machine Learning Engineer jobs in Las Vegas, NV look for?

The top searched job categories for Entry Level Machine Learning Engineer jobs in Las Vegas, NV are:

What cities near Las Vegas, NV are hiring for Entry Level Machine Learning Engineer jobs?

Cities near Las Vegas, NV with the most Entry Level Machine Learning Engineer job openings:

Infographic showing various Entry Level Machine Learning Engineer job openings in Las Vegas, NV as of August 2026, with employment types broken down into 77% Full Time, and 23% Contract. Highlights an 92% In-person, and 8% Remote job distribution, with an average salary of $66,662 per year, or $32 per hour.

Bruno Rossi Distinguished Postdoctoral Fellowship

Mission Support and Test Services, LLC

North Las Vegas, NV • On-site

$45K - $61K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted 26 days ago


Job description


Mission Support and Test Services, LLC (MSTS) manages and operates the Nevada National Security Site (NNSS) for the U.S. National Nuclear Security Administration (NNSA). Our MISSION is to help ensure the security of the United States and its allies by providing high-hazard experimentation and incident response capabilities through operations, engineering, education, field, and integration services and by acting as environmental stewards to the Site's Cold War legacy. Our VISION is to be the user site of choice for large-scale, high-hazard, national security experimentation, with premier facilities and capabilities below ground, on the ground, and in the air. (See NNSS.gov for our unique capabilities.) Our 2,750+ professional, craft, and support employees are called upon to innovate, collaborate, and deliver on some of the more difficult nuclear security challenges facing the world today.
  • MSTS offers our full-time employees highly competitive salaries and benefits packages including medical, dental, and vision; both a pension and a 401k; paid time off and 96 hours of paid holidays; relocation (if located more than 75 miles from work location); tuition assistance and reimbursement; and more.
  • MSTS is a limited liability company consisting of Honeywell International Inc. (Honeywell), Jacobs Engineering Group Inc. (Jacobs), and HII Nuclear Inc.

Responsibilities
The NNSS Science & Technology Directorate invites exceptional early-career scientists to apply for the Bruno Rossi Distinguished Postdoctoral Fellowship. The Rossi Fellow will drive advances in the theory, computational modeling, and/or machine-learning applications to the Scorpius linear induction accelerator (LIA) - one of the Nation's flagship capabilities supporting NNSA missions. This is a high-impact, publication-friendly role embedded with a senior NNSS mentor and collaborating laboratories.
Fellowship Focus Areas (Theory/Computation/ML)
We are seeking exceptional early-career PhD scientists or engineers with expertise in accelerator physics and a passion for applying data science, artificial intelligence (AI), and machine learning (ML) to model, control, and optimize complex systems. We also welcome applicants with a strong background in computational science who are eager to apply their skills to challenges in accelerator science. In particular, fellows will be fully supported to lead a research program focused on one or more of the following areas.
A. Accelerator & Beam Physics (Theory/Computation)
• Relativistic Beam-Target Interaction Physics: Investigating beam interactions with complex bremsstrahlung converters, including X-ray source modeling, dose and fluence optimization, and converter survivability under advanced material responses.
• Beam Transport in Complex Environments: Studying beam transport in solenoidal and induction systems, with emphasis on emittance preservation, halo formation and mitigation, and energy spread control under realistic operating conditions.
• Collective Effects and Instabilities: Developing models and mitigation strategies for phenomena such as Beam Breakup (BBU), corkscrew motion, and transverse/longitudinal impedance-driven instabilities.
  • Pulsed-Power and Accelerator Coupling: Exploring circuit-beam co-simulation, magnet and induction module dynamics, and timing and waveform shaping to enhance stability and brightness.
  • Diagnostics by Design: Creating inference methods and synthetic diagnostics to extract critical machine parameters-such as emittance, current, energy, spot size, and centroid motion-from limited data, while incorporating uncertainty quantification and error budgets for machine studies.
    • Multiphysics Target Response: Modeling the Magneto-Hydrodynamics (MHD) and thermomechanics of converter materials under intense pulsed loading, including shock and thermal fatigue, to evaluate lifetime and performance trade-offs.

Representative tools and methods: Particle-In-Cell (PIC) and Vlasov-Fokker-Planck simulations, hybrid PIC-fluid models, envelope and moment techniques, Monte Carlo radiation transport, surrogate modeling, adjoint and gradient-based optimization, as well as rigorous uncertainty quantification (UQ) and sensitivity analysis.
B. Machine Learning, Artificial Intelligence, and Digital Twin Foundations for the Scorpius Accelerator
• Data-Driven Machine Tuning: Optimizing accelerator performance by leveraging cutting-edge methods to rapidly identify optimal set points and compensate for beam drifting across multiple shots and variable thermal states.
  • Predictive Maintenance and Anomaly Detection: Applying time-series modeling to pulsed-power components and beam diagnostics for fault prediction, remaining useful life estimation, and automated alert systems.
  • Physics-Constrained Machine Learning: Implementing novel neural network architectures and reduced-order modeling techniques, constrained by first-principles physics, to deliver fast and explainable predictions.
  • Uncertainty-Aware Control: Developing decision-making frameworks with calibrated posteriors to ensure safe operation, while building digital twin architectures and data pipelines that integrate simulation, controls, and diagnostics in near-real time.

Successful applicants will be expected to demonstrate a sophisticated understanding of these methodologies. This includes a meticulous selection of appropriate techniques, awareness of their inherent limitations.
Impact
This fellowship offers a distinguished opportunity to drive transformative innovation at the forefront of accelerator science. The Rossi Fellow will be instrumental in developing and demonstrating next-generation capabilities for the Scorpius accelerator and allied radiographic systems. This foundational work is critical for achieving enhanced brightness, stability, system responsiveness, and long-term reliability, directly reinforcing the strategic imperatives of NNSA's stockpile stewardship mission. The Fellow's research will provide a definitive basis for optimizing machine studies, informing strategic hardware development, and accelerating the realization of the full Scorpius digital twin
Application Materials
Please combine materials into a single PDF when possible:
  1. Curriculum Vitae (with education, publications, software contributions, and up to three references to key codes or datasets).
  2. Research Statement (≤ 3 pages): proposed 2-3 projects aligned to Focus Areas; include methods, anticipated milestones, and potential collaborators.
  3. Selected Publications or preprints demonstrating relevant expertise.
  4. References: contact information for 3-5 referees. (Letters may be requested at the shortlist stage.)

Interviews: Finalists will be invited for a two-day on-site interview, including a technical seminar on current work and proposed research.
How to Apply & Key Dates:
  • Deadline for full consideration: October 31, 2026, 11:59 PM Pacific Time
  • Interviews: November-December 2026
  • Decisions: January 2027
  • Start date: 2027 (flexible)

Compensation & Support
  • Annual salary: $130,000
  • Research support: Up to $250,000 across the term for R&D expenses as described above, allocated annually with NNSS mentor and program approval. Discretionary research support across the fellowship for hardware, software, data/storage, user facility access, travel, and-subject to policy and need-the ability to fund a graduate student or research associate.
  • Term & Support
    - Term: Up to 3 years (initial 2-year appointment with a 3rd-year extension based on performance and program needs).
    - Mentorship & Visibility: Dedicated NNSS mentor; opportunities to present to NNSS/NNSA leadership and partner labs (LANL, LLNL) and to publish in peer-reviewed venues consistent with program requirements.

About the Fellowship & Namesake
The fellowship honors Bruno Benedetto Rossi (1905-1993), a trailblazing experimental and theoretical physicist whose career helped shape modern particle physics, space plasma physics, and x-ray astronomy. Trained at the University of Bologna, and having collaborated with Niels Bohr in Denmark, Patrick Blackett at the University of Manchester, and Enrico Fermi at the University of Chicago, Rossi later became a professor at MIT. There, he pioneered the electronic coincidence method, which enabled unambiguous detection of rare, fast events and opened the door to modern high-energy instrumentation.
His early work established the charged nature of cosmic rays, mapped their latitude/altitude effects, and revealed extensive air showersproduced by ultra-high-energy primaries.
During the Manhattan Project, Rossi led diagnostic development at Los Alamos, including fast ionization chambers and timing methods crucial to understanding implosion dynamics. After the war, he founded the renowned MIT Cosmic Ray Group, which evolved into the Center for Space Research. Rossi's group instrumented early space missions that characterized the solar wind, and he championed the first detections that launched x-ray astronomy, demonstrating that the universe is bright in high-energy photons.
The Rossi Fellow carries forward this legacy: rigorous physics, elegant instrumentation by model and algorithm, and science in service to national missions.
For More Information
Learn more about the fellowship and its namesake at the NNSS page: https://nnss.gov/mission/sdrd/bruno-rossi-distinguished-postdoctoral-fellowship-in-science-and-technology/
Qualifications
Eligibility
  • PhD in a STEM discipline (physics, applied physics, nuclear engineering, EE, applied math, CS, or related field) awarded within 3 years of the start date, or all requirements completed by the start date.
  • Demonstrated excellence in at least one of: high-performance scientific computing; accelerator/beam physics; radiation transport; pulsed-power modeling; multiphysics MHD; optimization/UQ; or modern ML/AI for physical systems.
  • Strong written and oral communication skills and the ability to collaborate across disciplines.
  • Demonstrated experience in building successful collaborations across multiple organizations.
  • Effective verbal and written communication skills necessary to collaborate in a team environment
  • and to present and explain technical information to stakeholders.
  • Experience working independently, as well as in a team, with minimal direction in a driven environment
  • Primary duty location is the NNSS' North Las Vegas facility with occasional travel to the NNSS site, LANL, LLNL, and SNL.
  • A 4/10 work schedule (Mon-Thu) is typical and subject to change. Limited hybrid arrangements may be considered depending on program needs and security requirements.
  • Pre-placement physical examination, which includes a drug screen, is required. MSTS maintains a substance abuse policy that includes random drug testing.
  • Must possess a valid driver's license.

MSTS is required by DOE directive to conduct a pre-employment drug test and background review that includes checks of personal references, credit, law enforcement records, and employment/education verifications. Applicants offered employment with MSTS are also subject to a federal background investigation to meet the requirements for access to classified information or matter if the duties of the position require a DOE security clearance. Substance abuse or illegal drug use, falsification of information, criminal activity, serious misconduct or other indicators of untrustworthiness can cause a clearance to be denied or terminated by DOE, resulting in the inability to perform the duties assigned and subsequent termination of employment. In addition, Applicants for employment must be able to obtain and maintain a DOE Q-level security clearance, which requires U.S. citizenship, at least 18 years of age. Reference DOE Order 472.2, "Personnel Security". If you hold more than one citizenship (i.e., of the U.S. and another country), your ability to obtain a security clearance may be impacted.
Department of Energy Q Clearance (position will be cleared to this level). Reviews and tests for the absence of any illegal drug as defined in 10 CFR Part 707.4, "Workplace Substance Abuse Programs at DOE Sites," will be conducted. Applicant selected will be subject to a Federal background investigation, required to participate in subsequent reinvestigations, and must meet the eligibility requirements for access to classified matter. Successful completion of a counterintelligence evaluation, which may include a counterintelligence-scope polygraph examination, may also be required. Reference 10 CFR Part 709, "Counterintelligence Evaluation Program."
MSTS is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, national origin, disability, veteran status or other characteristics protected by law. MSTS is a background screening, drug-free workplace.