... RLHF, edge AI, XAI, GPU acceleration) • Partner with Program Manager and Project Engineer to define staffing, data, schedules, and resources required to execute JTF Sierra technical initiatives • ...
... RLHF, edge AI, XAI, GPU acceleration) • Partner with Program Manager and Project Engineer to define staffing, data, schedules, and resources required to execute JTF Sierra technical initiatives • ...
Staff Applied AI/ML Scientist
Denver, CO · On-site
$158 - $237/hr
Experience with local training (pre-training / fine-tuning / RLHF / post-training) of open-weights autoregressive large language models like GLM, Qwen, Gemma, LLaMA, etc. * Experience with open ...
Staff Applied AI/ML Scientist
Denver, CO · On-site
$158 - $237/hr
Experience with local training (pre-training / fine-tuning / RLHF / post-training) of open-weights autoregressive large language models like GLM, Qwen, Gemma, LLaMA, etc. * Experience with open ...
Rlhf information
What is an RLHF job?
An RLHF (Reinforcement Learning with Human Feedback) job involves training AI models using human feedback to improve their responses. Professionals in this role analyze model outputs, provide evaluations, and refine AI behavior through reinforcement learning techniques. These roles are common in AI research, content moderation, and chatbot development.
What are the key skills and qualifications needed to thrive as a Reinforcement Learning from Human Feedback (RLHF) engineer, and why are they important?
To thrive as an RLHF Engineer, you need a strong background in machine learning, reinforcement learning, and programming (often Python), typically supported by an advanced degree in computer science or a related field. Experience with ML frameworks (such as TensorFlow or PyTorch), data annotation tools, and familiarity with large language models are typically required. Strong analytical thinking, collaboration, and clear communication are essential soft skills to succeed in research-driven, interdisciplinary teams. These skills and qualities are crucial for developing safe, effective AI systems that integrate human feedback and adapt to complex real-world tasks.
What are some common challenges faced by professionals working in Reinforcement Learning from Human Feedback (RLHF) roles?
Professionals in RLHF roles often encounter challenges related to data quality and alignment between human feedback and model behavior. Collecting consistent, unbiased feedback from human annotators can be complex, and ensuring that the reinforcement learning model interprets this feedback correctly requires careful design of reward functions and training protocols. Additionally, balancing the need for rapid experimentation with maintaining rigorous evaluation standards is crucial. Collaboration with interdisciplinary teams, including data scientists, ML engineers, and domain experts, is common to address these challenges and improve model alignment.
What is the difference between Rlhf vs Rn?
| Aspect | Rlhf | Rn |
|---|---|---|
| Required Credentials | Licensed healthcare professional, often with specialized training in mental health or behavioral health | Licensed practical nurse or registered nurse, with nursing licensure and possibly additional certifications |
| Work Environment | Behavioral health facilities, clinics, hospitals, or community health settings | Hospitals, clinics, long-term care facilities, and community health settings |
| Employer & Industry Usage | Behavioral health and mental health services | General healthcare and nursing services |
| Common Search & Comparison | Rlhf vs Rn | Rlhf vs Rn |
While Rlhf (Registered Licensed Mental Health Facilitator) focuses on mental health support and behavioral health interventions, Rn (Registered Nurse) provides broader nursing care across various medical settings. Both roles require licensure, but Rlhf specializes in mental health, whereas Rn covers general patient care.
What are the most commonly searched types of Rlhf jobs in Colorado?
The most popular types of Rlhf jobs in Colorado are:
What are popular job titles related to Rlhf jobs in Colorado?
For Rlhf jobs in Colorado, the most frequently searched job titles are:
What job categories do people searching Rlhf jobs in Colorado look for?
The top searched job categories for Rlhf jobs in Colorado are:
What cities in Colorado are hiring for Rlhf jobs?
Cities in Colorado with the most Rlhf job openings:
Principal AI/ML Engineer with Security Clearance
Centennial, CO • On-site
Contractor
Re-posted 19 days ago
Job description
Duties: Location Englewood, Colorado Hybrid opportunity Will need to be able to obtain a clearance This is a Contract opportunity In this role, you will help shape the long-term AI/ML technical vision for the organization, guide high-impact R&D initiatives, and lead the development of advanced autonomy, perception, analytics, and generative AI capabilities.
You will be responsible for setting technical direction across multiple simultaneous efforts, defining architectural standards, and ensuring that JTF Sierra’s prototypes and initiatives represent industry-leading innovation.
This role requires exceptional technical depth, the ability to operate with extreme autonomy, and the leadership presence to influence engineering culture, collaborate with program leadership, mentor staff, and represent the team to senior executives, customers, and external partners.
Role Expectations Specific to This Team • Translate broad mission objectives into program-level AI/ML architectures, strategies, staffing needs, data plans, and technical frameworks
• Drive system-level AI/ML decision-making, establishing technical standards and guiding engineering trade studies that shape platform-level autonomy and perception capabilities
• Identify and champion high-value R&D opportunities, emerging technologies, and cross-organizational partnerships that accelerate SNC’s AI/ML advancements
• Provide deep technical consultation across JTF Sierra and adjacent Business Units product lines, ensuring architectural coherence and technical excellence
• Ensure AI/ML solutions are architected for scalability and integration with enterprise-wide platforms, collaborating with IT and infrastructure teams to define and implement the necessary tools. Data pipeline, and computing resources for sustainable AI/ML operations across the organization.
• Balance program-specific AI/ML solution development with strategic focus on establishing reusable frameworks, common data assets, and infrastructure that support cross-program and enterprise-wide AI/ML adoption
Skills: • Lead design and technical direction for next-generation architectures spanning deep learning, reinforcement learning, multimodal generative AI, and advanced perception/decision systems
• Architect and oversee end-to-end multi-program AI/ML systems across platforms and embedded systems
• Assist with development of long-term technical strategies, roadmaps, and requirements for emerging AI/ML initiatives
• Identify, define, and advocate for the foundational data, compute, MLOps, and cloud/on-prem infrastructure necessary to support sustainable and secure AI/ML development and deployment across JTF Sierra and related business units.
• Establish and promote best practices for the full AI/ML lifecycle—including data management, model versioning, CI/CD for ML, monitoring, and continuous improvement—to ensure reliable deployment and operation of AI/ML models in production.
• Oversee multiple development streams, providing technical reviews, risk assessments, and mitigations plans
• Shape system-level behavior and engineering tradeoffs when requirements are ambiguous
• Lead development of simulations, sensor fusion models, vision models, and planning/decision algorithms
• Represent JTF Sierra to leadership, customers, and partners (assist in developing and presenting briefings, demos, high-level technical presentations, etc)
• Establish adaptive, agile AI/ML validation, verification, and safety frameworks for proof-of-concept level mission-critical systems
• Evaluate and introduce emerging technologies (examples: transformers, RLHF, edge AI, XAI, GPU acceleration)
• Partner with Program Manager and Project Engineer to define staffing, data, schedules, and resources required to execute JTF Sierra technical initiatives
• Coach and develop engineering talent, raising JTF Sierra’s overall AI/ML capabilities
Education: • Bachelor’s degree in Computer Science, Engineering, Math, Statistics, or related STEM field
• 14+ years of experience in AI/ML or related fields, or 16+ years without a degree
• Demonstrated mastery of deep learning, reinforcement learning, generative models, and large-scale AI/ML system architecture
• Proven experience architecting and deploying mission-critical and/or large-scale AI/ML systems
• Strong proficiency in Python, C++, C#, and/or Java with experience building scalable Machine Learning systems
• Experience providing technical leadership across teams, projects, or programs
• Ability to define technical strategies, influence senior stakeholders, and make organization-level architecture decisions
• In-depth experience with aerospace/defense-relevant regulatory and cybersecurity considerations
• Demonstrated ability to mentor and grow engineering talent within an organization
Qualifications We Prefer
• Advanced degree (MS or PhD) in AI/ML or related field
• Experience applying AI/ML to autonomy, multimodal sensor fusion, or embedded/real-time platforms
• Experience establishing or scaling ML engineering standard (MLOps, validation frameworks, data management)
• Expertise with GPU acceleration, CUDA/TensorRT, or parallel computing
• Publications, patents, or thought leadership in AI/ML
• Familiarity with edge AI, explainable AI (XAI), or emerging/advanced ML topics
• Experience translating high-level mission objectives into complex AI/ML system architectures (HMI scenarios, autonomy stacks)
You will be responsible for setting technical direction across multiple simultaneous efforts, defining architectural standards, and ensuring that JTF Sierra’s prototypes and initiatives represent industry-leading innovation.
This role requires exceptional technical depth, the ability to operate with extreme autonomy, and the leadership presence to influence engineering culture, collaborate with program leadership, mentor staff, and represent the team to senior executives, customers, and external partners.
Role Expectations Specific to This Team • Translate broad mission objectives into program-level AI/ML architectures, strategies, staffing needs, data plans, and technical frameworks
• Drive system-level AI/ML decision-making, establishing technical standards and guiding engineering trade studies that shape platform-level autonomy and perception capabilities
• Identify and champion high-value R&D opportunities, emerging technologies, and cross-organizational partnerships that accelerate SNC’s AI/ML advancements
• Provide deep technical consultation across JTF Sierra and adjacent Business Units product lines, ensuring architectural coherence and technical excellence
• Ensure AI/ML solutions are architected for scalability and integration with enterprise-wide platforms, collaborating with IT and infrastructure teams to define and implement the necessary tools. Data pipeline, and computing resources for sustainable AI/ML operations across the organization.
• Balance program-specific AI/ML solution development with strategic focus on establishing reusable frameworks, common data assets, and infrastructure that support cross-program and enterprise-wide AI/ML adoption
Skills: • Lead design and technical direction for next-generation architectures spanning deep learning, reinforcement learning, multimodal generative AI, and advanced perception/decision systems
• Architect and oversee end-to-end multi-program AI/ML systems across platforms and embedded systems
• Assist with development of long-term technical strategies, roadmaps, and requirements for emerging AI/ML initiatives
• Identify, define, and advocate for the foundational data, compute, MLOps, and cloud/on-prem infrastructure necessary to support sustainable and secure AI/ML development and deployment across JTF Sierra and related business units.
• Establish and promote best practices for the full AI/ML lifecycle—including data management, model versioning, CI/CD for ML, monitoring, and continuous improvement—to ensure reliable deployment and operation of AI/ML models in production.
• Oversee multiple development streams, providing technical reviews, risk assessments, and mitigations plans
• Shape system-level behavior and engineering tradeoffs when requirements are ambiguous
• Lead development of simulations, sensor fusion models, vision models, and planning/decision algorithms
• Represent JTF Sierra to leadership, customers, and partners (assist in developing and presenting briefings, demos, high-level technical presentations, etc)
• Establish adaptive, agile AI/ML validation, verification, and safety frameworks for proof-of-concept level mission-critical systems
• Evaluate and introduce emerging technologies (examples: transformers, RLHF, edge AI, XAI, GPU acceleration)
• Partner with Program Manager and Project Engineer to define staffing, data, schedules, and resources required to execute JTF Sierra technical initiatives
• Coach and develop engineering talent, raising JTF Sierra’s overall AI/ML capabilities
Education: • Bachelor’s degree in Computer Science, Engineering, Math, Statistics, or related STEM field
• 14+ years of experience in AI/ML or related fields, or 16+ years without a degree
• Demonstrated mastery of deep learning, reinforcement learning, generative models, and large-scale AI/ML system architecture
• Proven experience architecting and deploying mission-critical and/or large-scale AI/ML systems
• Strong proficiency in Python, C++, C#, and/or Java with experience building scalable Machine Learning systems
• Experience providing technical leadership across teams, projects, or programs
• Ability to define technical strategies, influence senior stakeholders, and make organization-level architecture decisions
• In-depth experience with aerospace/defense-relevant regulatory and cybersecurity considerations
• Demonstrated ability to mentor and grow engineering talent within an organization
Qualifications We Prefer
• Advanced degree (MS or PhD) in AI/ML or related field
• Experience applying AI/ML to autonomy, multimodal sensor fusion, or embedded/real-time platforms
• Experience establishing or scaling ML engineering standard (MLOps, validation frameworks, data management)
• Expertise with GPU acceleration, CUDA/TensorRT, or parallel computing
• Publications, patents, or thought leadership in AI/ML
• Familiarity with edge AI, explainable AI (XAI), or emerging/advanced ML topics
• Experience translating high-level mission objectives into complex AI/ML system architectures (HMI scenarios, autonomy stacks)