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Junior Ai Engineer Jobs in Reno, NV (NOW HIRING)

Sr AI/ML Engineer

Sparks, NV · On-site

$106K - $146K/yr

The Senior AI/ML Engineer is a highly skilled and experienced professional responsible for leading ... Demonstrated experience leading teams or projects, including mentoring junior staff. * Proven track ...

Senior Data Center Operations Engineer

Reno, NV · On-site

$105K - $143K/yr

Mentor and train junior operations staff; ensure proper documentation and SOP adherence ... AI/HPC workloads. * Well-trained team of operations staff that follows SOPs, executes work ...

CCoE, Cloud Architect

Reno, NV · On-site

$115K - $160K/yr

CCoE, Cloud Architect The Cloud and AI Center of Excellence is the technical resource for helping ... Certified Solutions Architect or Solutions Engineer in at least one of the major hyperscalers is ...

Junior Ai Engineer information

See Reno, NV salary details

$33.4K

$71.6K

$109.2K

How much do junior ai engineer jobs pay per year?

As of Aug 26, 2026, the average yearly pay for junior ai engineer in Reno, NV is $71,589.00, according to ZipRecruiter salary data. Most workers in this role earn between $48,400.00 and $79,800.00 per year, depending on experience, location, and employer.

What is a Junior AI Engineer?

A Junior AI Engineer is an entry-level professional who assists in the development and implementation of artificial intelligence models and systems. They typically work under the supervision of more experienced engineers to build, test, and deploy machine learning models, process data, and write code. Junior AI Engineers often collaborate with data scientists and software developers to integrate AI solutions into products or services. Their role is ideal for those with foundational knowledge in programming, mathematics, and machine learning concepts, looking to gain hands-on experience in the AI field.

What are the key skills and qualifications needed to thrive as a Junior AI Engineer?

To thrive as a Junior AI Engineer, you need a solid understanding of programming (especially Python), mathematics (linear algebra, statistics), and foundational machine learning concepts, often supported by a relevant degree or coursework. Familiarity with tools such as TensorFlow, PyTorch, and version control systems like Git is typically required, along with knowledge of cloud platforms like AWS or Azure. Strong problem-solving skills, willingness to learn, and effective teamwork and communication abilities help you stand out in this collaborative, fast-evolving field. These skills ensure you can contribute to AI projects efficiently, adapt to new technologies, and work well within multidisciplinary teams.

What are some typical challenges a Junior AI Engineer might face during their first year on the job?

As a Junior AI Engineer, you may encounter challenges such as understanding complex codebases, adapting to rapidly evolving AI frameworks, and balancing the need for innovation with production-level code quality. Collaborating with data scientists, senior engineers, and product managers to align on project goals and deliverables can also be a learning curve. Additionally, managing large datasets and debugging machine learning models require strong problem-solving skills and attention to detail, but these challenges offer excellent opportunities for growth and mentorship within your team.

What is the difference between Junior Ai Engineer vs Data Scientist?

AspectJunior Ai EngineerData Scientist
Required CredentialsBachelor's in CS, AI, or related field; some certificationsBachelor's or higher in CS, Statistics, or related; advanced certifications
Work EnvironmentDevelopment, coding, model implementationData analysis, modeling, insights generation
Employer & Industry UsageTech companies, startups, AI-focused firmsTech, finance, healthcare, research institutions

Junior Ai Engineers focus on developing and implementing AI models, often working closely with data and algorithms. Data Scientists analyze data to extract insights and build predictive models. While both roles require programming skills and a background in data or AI, Junior Ai Engineers are more involved in the technical development of AI systems, whereas Data Scientists focus on data analysis and interpretation.

What are the most commonly searched types of Ai Engineer jobs in Reno, NV?

The most popular types of Ai Engineer jobs in Reno, NV are:

What are popular job titles related to Junior Ai Engineer jobs in Reno, NV?

For Junior Ai Engineer jobs in Reno, NV, the most frequently searched job titles are:

What job categories do people searching Junior Ai Engineer jobs in Reno, NV look for?

The top searched job categories for Junior Ai Engineer jobs in Reno, NV are:

What cities near Reno, NV are hiring for Junior Ai Engineer jobs?

Cities near Reno, NV with the most Junior Ai Engineer job openings:

Infographic showing various Junior Ai Engineer job openings in Reno, NV as of August 2026, with employment types broken down into 75% Full Time, 22% Part Time, and 3% Contract. Highlights an 63% Physical, 4% Hybrid, and 33% Remote job distribution, with an average salary of $71,589 per year, or $34.4 per hour.

$106K - $146K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 21 days ago


Sierra Nevada Corporation rating

8.7

Company rating: 8.7 out of 10

Based on 29 frontline employees who took The Breakroom Quiz

16th of 72 rated aerospace companies


Job description

The Senior AI/ML Engineer is a highly skilled and experienced professional responsible for leading the development of complex AI/ML systems, driving innovation, and mentoring team members to deliver impactful solutions. In this role, you will oversee the design, implementation, and deployment of scalable AI/ML models for mission-critical aerospace and defense applications. You will also act as a technical leader, providing strategic guidance on AI/ML initiatives, ensuring compliance with regulatory standards, and collaborating with stakeholders to meet organizational objectives. This position demands advanced technical expertise and the ability to manage high-impact projects in a fast-paced environment.As SNC's corporate team, we provide the company and its business areas with strategic direction and business support spanning executive management, finance and accounting, operations, human resources, legal, IT, information security, facilities, marketing, and communications.

Responsibilities:

  • Exploration & Innovation:
    • Conduct continuous discovery and hypothesis-driven experimentation, rapidly developing prototypes to assess feasibility and potential impact.
    • Partner with business stakeholders to translate non-technical requirements into actionable AI/ML exploration paths.
  • RAG-Focused AI/ML Development:
    • Develop and prototype RAG-based architectures, including embedding pipelines, retrieval strategies, and transformer-based generative components.
    • Explore and validate new approaches for retrieval, indexing, and multimodal document understanding.
    • Apply validation, safety, and explainability practices in support of aerospace/defense requirements.
  • MPC & Real-Time Decisioning Exploration:
    • Design and prototype MPC-aligned models incorporating predictive modeling, optimization, and reinforcement-learning-based control.
    • Develop signal processing, perception, and planning pipelines supporting MPC control loops.
    • Use GPU acceleration, simulation environments, and HPC resources to support MPC experimentation.
  • Advanced AI/ML Modeling & Technical Leadership:
    • Architect, train, and optimize advanced models including transformers, GANs, RL agents, and real-time systems.
    • Provide technical leadership, mentor engineers, and guide cross-functional teams.
  • Safety, Validation & Integration Support:
    • Develop validation and testing frameworks ensuring compliance with safety and reliability standards.
    • Support integration teams with prototypes, documentation, and technical insights as required.

Qualifications You Must Have:

  • Bachelor's degree in computer science, mathematics, applied statistics, various engineering disciplines, or related STEM discipline
  • 10+ years of experience in a related field.
  • Relevant experience can be considered as a substitute for the required educational qualifications. In the absence of a degree, a minimum of 12 years of related experience is required.
  • Higher level relevant degree may substitute for experience.
  • Advanced skills in machine learning frameworks (TensorFlow, PyTorch) and modern AI/ML techniques, including supervised, unsupervised, and reinforcement learning (e.g., PPO, Actor/Critic). Demonstrated ability to design and optimize generative AI models (e.g., transformers) and neural networks for complex applications.
  • Extensive experience architecting, deploying, and optimizing AI/ML systems, including ANNs, CNNs, and RNNs, in large-scale or mission-critical environments. Led efforts to improve model performance and reliability in production settings.
  • Strong proficiency in programming languages such as Python, C++, C# or Java, with experience in building scalable AI/ML systems.
  • Demonstrated experience leading teams or projects, including mentoring junior staff.
  • Proven track record of deploying AI/ML models in production environments and optimizing them for real-world use cases.
  • Knowledge of regulatory and cybersecurity requirements for AI/ML systems in aerospace and defense applications.
  • Experience designing and optimizing generative AI models including transformers and GANs.
  • Experience building or integrating transformer-based models for retrieval-augmented or hybrid reasoning systems.
  • Proficiency designing embedding, retrieval, or indexing pipelines for large, multi-source datasets.
  • Familiarity with explainable AI (XAI) techniques for safety-critical environments.
  • Hands-on experience with reinforcement learning and real-time systems applicable to MPC.

Qualifications We Prefer:

  • Master's degree + additional years experience, or Ph.D. in Artificial Intelligence, Machine Learning, or a related field.
  • Experience with hardware acceleration technologies (e.g., CUDA, TensorRT) and high-performance computing systems.
  • Background in autonomous systems, robotics, or sensor fusion.
  • Familiarity with Agile/DevOps methodologies for software development.
  • Certifications in AI/ML or related fields, such as AWS Certified Machine Learning Specialty or Google Professional Machine Learning Engineer.
  • Deep understanding and practical application of Agile/DevOps in large-scale AI/ML projects.
  • Demonstrated experience with reinforcement learning and generative AI models in production or research settings.
  • Advanced proficiency in GPU programming, parallel/distributed computing, and optimizing ML workloads for performance.
  • Expertise in designing and implementing complex ML pipelines, including clustering, dimensionality reduction, generative modeling, and reinforcement learning, aligned to mission objectives and HMI systems.
  • Skilled in analyzing massive, multi-source datasets and delivering end-to-end autonomy software solutions, from requirements to deployment and maintenance.
  • Working knowledge of hardware acceleration technologies (CUDA, TensorRT), edge AI deployments, and explainable AI (XAI) methods.
  • Exposure to or interest in quantum computing for ML applications.

Essential Functions:


  • Contribute to AI/ML innovation and prototyping projects from exploration through technical feasibility assessment.
  • Support cross-functional engineering teams and integration efforts as needed.
  • Travel occasionally (10-20%) to customer sites, test facilities, or conferences.
  • Work in a hybrid office environment, balancing hands-on research with technical leadership.
  • Ensure compliance with safety, regulatory, and cybersecurity standards for AI/ML systems.

This posting will be open for application for a minimum of 5 days and may be extended based on business needs.

Estimated Starting Salary Range: $143,487.14 - $197,294.82. Compensation varies depending on a wide array of factors, such as candidates' key skills, relevant work experience, and education/training/certifications. The disclosed range estimate may be adjusted for any applicable geographic differential associated with the location at which the position may be filled.

SNC offers annual incentive pay based upon performance that is commensurate with the level of the position.

SNC offers a generous benefit package, including medical, dental, and vision plans, 401(k) with 150% match up to 6%, life insurance, 3 weeks paid time off, tuition reimbursement, and more.

IMPORTANT NOTICE:

This position requires the ability to obtain and maintain a Secret U.S. Security Clearance. U.S. Citizenship status is required as this position needs an active U.S. Security Clearance for employment. Non-U.S. citizens may not be eligible to obtain a security clearance. The Department of Defense Consolidated Adjudications Facility (DoD CAF), a federal government agency, handles the adjudicative aspects of the security clearance eligibility process for industry applicants. Adjudicative factors which affect the outcome of the eligibility determination include, but are not limited to, allegiance to the U.S., foreign influence, foreign preference, criminal conduct, security violations and illegal drug use.

Learn more about the background check process for Security Clearances.

SNC is a global leader in aerospace and national security committed to moving the American Dream forward. We're known and respected for our mission and execution focus, agility, and disruptive and rapid innovation. We provide leading edge technologies and transformative solutions that support our nation's most critical security needs. If you are mission-focused, thrive in collaborative environments, and want to make our country stronger with state-of-the-art technologies that safeguard freedom, join our team!

SNC is an Equal Opportunity Employer committed to an environment free of discrimination. Employment decisions are made based on merit without regard to race, color, age, religion, sex, national origin, disability, status as a protected veteran or other characteristics protected by law.


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