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Postdoctoral In Reinforcement Learning Jobs in Colorado

Sr AI/ML Engineer

Longmont, CO · On-site

$103K - $141K/yr

Advanced skills in machine learning frameworks (TensorFlow, PyTorch) and modern AI/ML techniques, including supervised, unsupervised, and reinforcement learning (e.g., PPO, Actor/Critic)

New

Sr. AI Engineer

Lone Tree, CO · On-site

$106K - $146K/yr

Advanced skills in machine learning frameworks (TensorFlow, PyTorch) and modern AI/ML techniques, including supervised, unsupervised, and reinforcement learning (e.g., PPO, Actor/Critic)

New

AI Engineer III

Lone Tree, CO · On-site

$58.75 - $79/hr

Proficient in machine learning frameworks (e.g., TensorFlow, PyTorch) and skilled in implementing advanced AI/ML techniques, such as supervised, unsupervised, and reinforcement learning (e.g., PPO ...

AI Engineer III

Highlands Ranch, CO · On-site

$56.50 - $76/hr

Proficient in machine learning frameworks (e.g., TensorFlow, PyTorch) and skilled in implementing advanced AI/ML techniques, such as supervised, unsupervised, and reinforcement learning (e.g., PPO ...

AI Engineer III

Lone Tree, CO · On-site

$58.75 - $79/hr

Proficient in machine learning frameworks (e.g., TensorFlow, PyTorch) and skilled in implementing advanced AI/ML techniques, such as supervised, unsupervised, and reinforcement learning (e.g., PPO ...

Proficient in machine learning frameworks (e.g., TensorFlow, PyTorch) and skilled in implementing advanced AI/ML techniques, such as supervised, unsupervised, and reinforcement learning (e.g., PPO ...

Principal AI/ML Engineer

Englewood, CO · On-site

$75 - $80.15/hr

Deep expertise in: * AI/ML system architecture * Deep learning * Reinforcement learning * Generative AI and foundation models * Large-scale machine learning systems * Strong programming skills in one ...

New

Sr. AI Engineer

Lone Tree, CO · On-site

$106K - $146K/yr

Advanced skills in machine learning frameworks (TensorFlow, PyTorch) and modern AI/ML techniques, including supervised, unsupervised, and reinforcement learning (e.g., PPO, Actor/Critic)

New

Staff AI/ML Engineer

Aurora, CO · On-site

$98K - $206K/yr

Experience with LLMs, Transformers, YOLO, GANs, Reinforcement Learning * Linux and AWS experience * Experience with CUDA and Python libraries such as CuPy, Numba, CuSignal, CuDF, etc. * Experience in ...

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Showing results 1-20

Postdoctoral In Reinforcement Learning information

What is the difference between Postdoctoral In Reinforcement Learning vs Postdoctoral In Machine Learning?

AspectPostdoctoral In Reinforcement LearningPostdoctoral In Machine Learning
Required CredentialsPhD in Computer Science, AI, or related field; strong programming skills; research experience in reinforcement learningPhD in Computer Science, AI, or related field; strong programming skills; research experience in machine learning
Work EnvironmentAcademic labs, research institutions, industry R&D teams focused on reinforcement learning applicationsAcademic labs, research institutions, industry R&D teams working on various machine learning techniques
Industry UsagePrimarily in AI research, robotics, gaming, and autonomous systemsBroader applications including data analysis, predictive modeling, and AI research

Postdoctoral In Reinforcement Learning specializes in research related to decision-making algorithms and autonomous systems, whereas Postdoctoral In Machine Learning covers a wider range of AI techniques. Both roles require similar credentials but differ in focus and application areas.

What are the key skills and qualifications needed to thrive as a Postdoctoral Researcher in Reinforcement Learning, and why are they important?

To thrive as a Postdoctoral Researcher in Reinforcement Learning, you need a PhD in computer science or a related field, with deep expertise in machine learning, statistics, and algorithm development. Proficiency in programming languages such as Python, experience with deep learning frameworks (e.g., TensorFlow or PyTorch), and familiarity with reinforcement learning libraries are typically required. Strong analytical thinking, problem-solving ability, collaboration, and scientific communication skills help you excel in research teams and publish impactful work. These competencies are vital to advancing state-of-the-art research, developing novel algorithms, and contributing to the academic and industrial progress in AI.

What are some common challenges faced by postdoctoral researchers in reinforcement learning, and how can they be addressed?

Postdoctoral researchers in reinforcement learning often face challenges such as balancing independent research projects with collaborative work, staying up-to-date with rapidly evolving literature, and managing the pressure to publish in top conferences. Effective time management, regular engagement with the research community through seminars and workshops, and seeking mentorship from senior colleagues can help address these challenges. Additionally, collaborating with interdisciplinary teams can offer fresh perspectives and support, making it easier to navigate complex research problems.

What is a Postdoctoral Researcher in Reinforcement Learning?

A Postdoctoral Researcher in Reinforcement Learning is an individual who has completed a PhD and conducts advanced research in the field of reinforcement learning, a branch of artificial intelligence focused on how agents take actions in environments to maximize rewards. These researchers often work in academic, industrial, or governmental research settings, collaborating on projects that advance the theoretical foundations or practical applications of reinforcement learning. Their responsibilities may include designing experiments, developing algorithms, publishing papers, and mentoring graduate students.
What are popular job titles related to Postdoctoral In Reinforcement Learning jobs in Colorado? For Postdoctoral In Reinforcement Learning jobs in Colorado, the most frequently searched job titles are:
What job categories do people searching Postdoctoral In Reinforcement Learning jobs in Colorado look for? The top searched job categories for Postdoctoral In Reinforcement Learning jobs in Colorado are:
What cities in Colorado are hiring for Postdoctoral In Reinforcement Learning jobs? Cities in Colorado with the most Postdoctoral In Reinforcement Learning job openings:
Sr AI/ML Engineer

$103K - $141K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 6 days ago

New


Sierra Nevada Corporation rating

8.7

Company rating: 8.7 out of 10

Based on 28 frontline employees who took The Breakroom Quiz

13th of 61 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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