1

Phd Computer Science Jobs in Nevada (NOW HIRING)

MS/PhD in Computer Science, Machine Learning, or a related field. * Background in autonomous driving, robotics, or complex real-time decision-making systems. * Experience with massive-scale ML data ...

MS/PhD in Computer Science, Machine Learning, or a related field. * Background in autonomous driving, robotics, or complex real-time decision-making systems. * Experience with massive-scale ML data ...

Required : • Bachelor's degree in Computer Science, Statistics, Data Science, Information Systems ... Preferred : • Advanced degrees such as Masters or PhD are preferred • Certifications in AI/ML ...

Required : • Bachelor's degree in Computer Science, Statistics, Data Science, Information Systems ... Preferred : • Advanced degrees such as Masters or PhD are preferred • Certifications in AI/ML ...

AI Engineer Senior Consultant

Las Vegas, NV · Hybrid

$99.80K - $137.10K/yr

Bachelor's degree in a STEM field (e.g., Computer Science, Engineering, Statistics, Data Science ... Advanced degree (MS/PhD) and/or relevant certifications (cloud and AI/ML). * 4+ years of experience ...

Bachelor's degree in a STEM field (e.g., Computer Science, Engineering, Statistics, Data Science ... Advanced degree (MS/PhD) and/or relevant certifications (cloud and AI/ML). * 2+ years of experience ...

AI Data Engineer - Senior Consultant

Las Vegas, NV · Hybrid

$99.80K - $137.10K/yr

Bachelor's degree in a STEM field (e.g., Computer Science, Engineering, Statistics, Data Science ... Advanced degree (MS/PhD) and/or relevant certifications (cloud and AI/ML). * 4+ years of experience ...

Bachelor's degree in a STEM field (e.g., Computer Science, Engineering, Statistics, Data Science ... Advanced degree (MS/PhD) and/or relevant certifications (cloud and AI/ML). * 4+ years of experience ...

next page

Showing results 1-20

Phd Computer Science information

See Nevada salary details

$57.5K

$84.6K

$99.8K

How much do phd computer science jobs pay per year?

As of May 30, 2026, the average yearly pay for phd computer science in Nevada is $84,630.00, according to ZipRecruiter salary data. Most workers in this role earn between $78,900.00 and $95,200.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a PhD in Computer Science, and why are they important?

To thrive as a PhD in Computer Science, you need advanced expertise in algorithms, programming, and research methodologies, typically supported by a doctoral degree in computer science or a related field. Mastery of programming languages (such as Python, Java, or C++), data analysis tools, and familiarity with version control systems like Git are commonly required, along with experience in publishing academic research. Critical thinking, problem-solving, strong written and verbal communication, and perseverance are vital soft skills for success in research and collaboration. These skills and qualifications are essential for making significant contributions to the field, driving innovation, and effectively sharing knowledge with the academic and professional community.

What are some common challenges faced by PhD Computer Science students during their research?

PhD Computer Science students often encounter challenges such as defining a clear and impactful research problem, managing long-term projects with limited guidance, and coping with the pressure to publish in top-tier conferences or journals. Balancing coursework, teaching responsibilities, and research can also be demanding. Effective time management, networking with peers and mentors, and seeking regular feedback can help students navigate these challenges and achieve their academic goals.

What is a PhD in Computer Science?

A PhD in Computer Science is the highest academic degree in the field, focused on advanced research and the creation of new knowledge in computing. It typically involves several years of coursework followed by original research culminating in a dissertation. Graduates often pursue careers in academia, research, or advanced industry roles that require deep technical expertise and problem-solving skills.

Is IT worth doing a PhD in CS?

A PhD in Computer Science can be valuable for careers in research, academia, or specialized industry roles requiring advanced expertise. It typically involves several years of study, research, and publication, and can lead to higher-level positions but may not be necessary for most industry jobs that value practical skills and experience. Consider your career goals and whether the research focus aligns with your interests before pursuing a PhD.
What are popular job titles related to Phd Computer Science jobs in Nevada? For Phd Computer Science jobs in Nevada, the most frequently searched job titles are:
What cities in Nevada are hiring for Phd Computer Science jobs? Cities in Nevada with the most Phd Computer Science job openings:
Infographic showing various Phd Computer Science job openings in Nevada as of May 2026, with employment types broken down into 3% As Needed, 57% Full Time, 21% Part Time, 16% Contract, and 3% Nights. Highlights an 58% Physical, 6% Hybrid, and 36% Remote job distribution, with an average salary of $84,630 per year, or $40.7 per hour.
Senior Machine Learning Engineer, Data Mining

Senior Machine Learning Engineer, Data Mining

Motional

Las Vegas, NV • On-site

$117K - $154.20K/yr

Full-time

Medical, Dental, Vision, Life, Retirement

Posted 18 days ago


Job description

Mission Summary:
At Motional, we're transforming how autonomous vehicles discover critical intelligence hidden within petabytes of multimodal sensor data. Our next-generation autonomous driving stack depends on finding the rare edge cases, long-tail scenarios, and model errors that matter most. Omnitag, our ML-powered multimodal data mining framework, is the engine that powers this discovery.
As a Senior Machine Learning Engineer on the Data Mining team, your mission is to build the "Brain" of this engine: designing massive multimodal Teacher models that understand the world, and distilling them into hyper-efficient Student models that can scour exabytes of data in near real-time. You will work at the intersection of large-scale representation learning, retrieval optimization, and reasoning systems. Your work will directly influence how we compress knowledge into efficient encoders for fast search, and how we apply reinforcement learning to optimize data discovery workflows and intelligent querying. By building smarter mining tools, you will accelerate the entire model improvement lifecycle for teams working on post-training analysis, error diagnosis, and dataset curation.
What You'll Do:
  • Architect and Train Distilled Models: Design and implement teacher-student model frameworks for multimodal sensor data. Develop training pipelines for knowledge distillation. Ensure student models maintain high accuracy while drastically reducing inference latency and memory footprint.
  • Reinforcement Learning for Data Discover: Build RL-based policy learning and reasoning systems for autonomous driving applications. Implement and scale RL training workflows (e.g., PPO, DQN, actor-critic methods) for simulation and real-world interaction. Explore reward shaping, environment modeling, and multi-agent RL where applicable.
  • Optimize Model Deployment for Real-Time Inference: Collaborate with backend engineers to deploy distilled and RL models into production. Optimize for latency, throughput, and hardware efficiency across GPU/CPU clusters. Implement model versioning, A/B testing, and monitoring for performance regressions.
  • Research and Integrate Agentic Systems: Explore and prototype agentic workflows for autonomous reasoning, chain-of-thought prompting, and goal-directed behavior. Integrate such systems into our broader autonomy stack as experimental or production components.
  • Drive Production Reliability: Establish patterns for graceful degradation, fault tolerance, and cost optimization. Operate Omnitag as a mission-critical data platform serving the entire ML organization, with a focus on reliability, debuggability, and operational excellence.
  • Mentor and Collaborate: Work closely with ML scientists, data engineers, and autonomy teams to translate research advances into scalable engineering solutions. Guide junior engineers in best practices for model training, evaluation, and deployment.

What We're Looking For:
  • BS in Computer Science, Machine Learning, or related field, or equivalent professional experience.
  • 6+ years of hands-on experience in machine learning engineering, with a focus on model post training, optimization, and deployment.
  • Strong experience with model distillation or teacher-student training - practical knowledge of loss functions, training strategies, and evaluation of compressed models.
  • Proven experience with reinforcement learning in production or research settings: policy optimization, reward design, simulation environments, and RL-based reasoning.
  • Expert-level proficiency in Python and ML frameworks (PyTorch, TensorFlow, or JAX).
  • Strong software engineering fundamentals: testing, CI/CD, containerization, and system design.
  • Experience deploying ML models in cloud environments (AWS, GCP, or Azure) and optimizing for inference.
  • Demonstrated ability to ship production-grade ML systems and mentor team members.
  • Demonstrated track record of shipping robust, well-tested, production-grade systems and mentoring junior engineers

Bonus Points (Nice-to-Haves):
  • MS/PhD in Computer Science, Machine Learning, or related field.
  • Experience with agentic systems, autonomous reasoning, chain-of-thought models, or LLM-based planning.
  • Background in autonomous driving, robotics, or real-time decision-making systems.
  • Familiarity with multimodal learning, sensor fusion, or embodied AI.
  • Experience building active learning loops, using the model to find the data that breaks the model.
  • Experience with ML-based data mining, active learning, or contrastive learning.
  • Knowledge of model serving tools (TF Serving, Triton, TorchServe) and MLOps platforms.
  • Publications or open-source contributions in RL, distillation, or efficient ML.

We encourage a hybrid schedule with in-office time at one of our locations in Boston, Pittsburgh, or Las Vegas to support collaboration, or this role can be fully remote.
The salary range for this role is an estimate based on a wide range of compensation factors including but not limited to specific skills, experience and expertise, role location, certifications, licenses, and business needs. The estimated compensation range listed in this job posting reflects base salary only. This role may include additional forms of compensation such as a bonus or company equity. The recruiter assigned to this role can share more information about the specific compensation and benefit details associated with this role during the hiring process.
Candidates for certain positions are eligible to participate in Motional's benefits program. Motional's benefits include but are not limited to medical, dental, vision, 401k with a company match, health saving accounts, life insurance, pet insurance, and more.
Salary Range
$172,000-$229,000 USD
Motional is a driverless technology company making autonomous vehicles a safe, reliable, and accessible reality. We're driven by something more.
Our journey is always people first.
We aren't just developing driverless cars; we're creating safer roadways, more equitable transportation options, and making our communities better places to live, work, and connect. Our team is made up of engineers, researchers, innovators, dreamers and doers, who are creating a technology with the potential to transform the way we move.
Higher purpose, greater impact.
We're creating first-of-its-kind technology that will transform transportation. To do so successfully, we must design for everyone in our cities and on our roads. We believe in building a great place to work through a progressive, global culture that is diverse, inclusive, and ensures people feel valued at every level of the organization. Diversity helps us to see the world differently; it's not only good for our business, it's the right thing to do.
Scale up, not starting up.
Our team is behind some of the industry's largest leaps forward, including the first fully-autonomous cross-country drive in the U.S, the launch of the world's first robotaxi pilot, and operation of the world's longest-standing public robotaxi fleet. We're driven to scale; we're moving towards commercialization of our technology, and we need team members who are ready to embrace change and challenges.
Formed as a joint venture between Hyundai Motor Group and Aptiv, Motional is fundamentally changing how people move through their lives. Headquartered in Boston, Motional has operations in the U.S and Asia. For more information, visit www.Motional.com and follow us on Twitter, LinkedIn, Instagram and YouTube.
Motional AD Inc. is an EOE. We celebrate diversity and are committed to creating an inclusive environment for all employees. To comply with Federal Law, we participate in E-Verify. All newly-hired employees are queried through this electronic system established by the DHS and the SSA to verify their identity and employment eligibility.