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Rlhf Jobs in Silver Spring, MD (NOW HIRING)

Quevera LLC

Software Engineer II

Herndon, VA · On-site

$100K - $137K/yr

Familiarity with supervised fine-tuning, instruction tuning, and RLHF/DPO alignment techniques. * Four (4) or more years of advanced Python development for machine learning workloads. * Strong ...

TheIncLab

AI Development Lead

Mclean, VA · On-site

Research & Innovation Impact Stay ahead of industry advancements in generative AI, foundational model tech, self-supervised learning, optimization techniques, RLHF, and robustness/interpretability.

TheIncLab

AI Development Lead

Mclean, VA · On-site

Research & Innovation Impact Stay ahead of industry advancements in generative AI, foundational model tech, self-supervised learning, optimization techniques, RLHF, and robustness/interpretability.

TheIncLab

AI Development Lead

Mclean, VA · On-site

Research & Innovation Impact Stay ahead of industry advancements in generative AI, foundational model tech, self-supervised learning, optimization techniques, RLHF, and robustness/interpretability.

10a Labs

Machine Learning Engineer

Washington, DC · On-site +1

$130K - $200K/yr

Experience with RLHF/RLAIF, reward modeling, policy optimization, or other model post-training techniques. * Experience evaluating frontier language or multimodal models. * Experience with ...

Bright Vision Technologies

Applied RL Engineer

Reston, VA · On-site

$100 - $150/hr

Experience with RLHF for large language models. * Familiarity with multi‑agent RL or hierarchical RL. * Exposure to robotics, control systems, or autonomous driving. * Publications in RL or related ...

Twenty

Applied AI Engineer

Washington, DC · On-site

... SFT, RLHF, DPO, PPO, GRPO). • You have experience curating, cleaning, and preprocessing datasets for training and evaluation. • You have working knowledge of relational, graph, and vector ...

10a Labs

Machine Learning Engineer

Washington, DC · On-site

$130K - $200K/yr

Experience with RLHF/RLAIF, reward modeling, policy optimization, or other model post-training techniques. * Experience evaluating frontier language or multimodal models. * Experience with ...

Citian

AI Integration Engineer

Washington, DC · On-site

$117K - $158K/yr

... RLHF, in-context-learning (ICL), and other applications. • Lead AI image recognition and computer vision strategies for infrastructure asset data extraction assessing model approaches, overseeing ...

Citian

AI Integration Engineer

Washington, DC

$117K - $158K/yr

Work closely with our Data team and specific datasets that can be used for continued pre-training, RLHF, in-context-learning (ICL), and other applications. * Lead AI image recognition and computer ...

Ordwaylabs

Lead Software Developer - CPQ

Washington, DC · On-site

$140 - $210/hr

Fine-tuning and RLHF concepts (not always hands-on, but expected knowledge) * Evaluation design -- building evals, benchmarks, and quality metrics * Shipped production AI features or agents * Strong ...

eSimplicity

Data Engineer II

Columbia, MD · On-site

$93K - $100K/yr

Familiarity with LLM evaluation frameworks, structured benchmarking, or human-in-the-loop refinement methods (e.g., RLHF-style workflows). * Expertise with advanced retrieval techniques such as ...

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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?

AspectRlhfRn
Required CredentialsLicensed healthcare professional, often with specialized training in mental health or behavioral healthLicensed practical nurse or registered nurse, with nursing licensure and possibly additional certifications
Work EnvironmentBehavioral health facilities, clinics, hospitals, or community health settingsHospitals, clinics, long-term care facilities, and community health settings
Employer & Industry UsageBehavioral health and mental health servicesGeneral healthcare and nursing services
Common Search & ComparisonRlhf vs RnRlhf 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 popular job titles related to Rlhf jobs in Silver Spring, MD?

For Rlhf jobs in Silver Spring, MD, the most frequently searched job titles are:

What job categories do people searching Rlhf jobs in Silver Spring, MD look for?

The top searched job categories for Rlhf jobs in Silver Spring, MD are:

What cities near Silver Spring, MD are hiring for Rlhf jobs?

Cities near Silver Spring, MD with the most Rlhf job openings:

Rlhf jobs near you
Infographic showing various Rlhf job openings in Silver Spring, MD as of August 2026, with employment types broken down into 76% Full Time, 5% Part Time, and 19% Contract. Highlights an 67% In-person, and 33% Remote job distribution.

Software Engineer II

Quevera LLC

Herndon, VA • On-site

$100K - $137K/yr

Full-time

Medical, Dental, Vision, Life, Retirement

Re-posted 24 days ago

Job description

Job Description:

Quevera is seeking a highly skilled Software Engineer II with an active TS/SCI clearance with Polygraph to support mission-critical programs. In this role, you will develop and optimize advanced machine learning solutions supporting multimodal artificial intelligence and computer vision applications for national security missions.

Working alongside applied scientists and engineering teams, you will design scalable machine learning pipelines, fine-tune Vision-Language Models (VLMs), build AWS-based training infrastructure, and develop data processing and evaluation frameworks for large-scale geospatial imagery datasets. You'll leverage modern AI technologies to deliver high-performing, secure, and production-ready machine learning solutions.

As a Software Engineer II, you'll have the opportunity to work with cutting-edge AI technologies, collaborate with industry experts, and contribute to innovative solutions supporting critical national security missions.


Work Schedule:

Work Location: Must be willing to work onsite in a SCIF daily, or as required.


Job Responsibilities:

  • Design and execute fine-tuning pipelines for Vision-Language Models (VLMs) using domain-specific imagery datasets.
  • Develop data preprocessing, training orchestration, and hyperparameter optimization workflows.
  • Build and implement evaluation frameworks for multimodal model performance, including image understanding, visual question answering, and spatial reasoning.
  • Develop scalable distributed training infrastructure using AWS services, including SageMaker and EC2 GPU instances.
  • Engineer data pipelines for curating, annotating, and transforming geospatial imagery into model-ready datasets.
  • Collaborate with applied scientists and solutions architects to optimize model architectures and parameter-efficient fine-tuning strategies, including LoRA and QLoRA.
  • Optimize model inference performance and deployment workflows.
  • Develop secure, scalable machine learning solutions that support mission requirements.


Minimum Requirements:

  • Active TS/SCI clearance with Polygraph required.
  • Current NGA eligibility with active SBU, SECNet, and COE accounts.
  • Five (5) or more years of professional machine learning engineering experience with a focus on deep learning.
  • One (1) or more years of experience fine-tuning large language models (LLMs) or Vision-Language Models (VLMs).
  • Experience with parameter-efficient fine-tuning techniques, including LoRA, QLoRA, and adapters.
  • Familiarity with supervised fine-tuning, instruction tuning, and RLHF/DPO alignment techniques.
  • Four (4) or more years of advanced Python development for machine learning workloads.
  • Strong proficiency with PyTorch and the Hugging Face ecosystem, including Transformers, PEFT, Datasets, and Accelerate.
  • Experience with distributed training frameworks such as DeepSpeed, FSDP, or Megatron.
  • Three (3) or more years of experience with computer vision or multimodal AI models.
  • Understanding of Vision Transformer architectures, including ViT, CLIP, LLaVA, or similar models.
  • Experience processing and augmenting image datasets at scale.
  • Three (3) or more years of experience with AWS machine learning infrastructure, including SageMaker, EC2 GPU instances, and Amazon S3.
  • Experience building machine learning evaluation pipelines, including automated benchmarking, metric computation, and result analysis.
  • Strong software engineering fundamentals, including version control, testing, and CI/CD practices for machine learning workflows.


Desired Skills:

  • Active TS/SCI clearance with Polygraph required.
  • Current NGA eligibility with active SBU, SECNet, and COE accounts.
  • Five (5) or more years of professional machine learning engineering experience with a focus on deep learning.
  • One (1) or more years of experience fine-tuning large language models (LLMs) or Vision-Language Models (VLMs).
  • Experience with parameter-efficient fine-tuning techniques, including LoRA, QLoRA, and adapters.
  • Familiarity with supervised fine-tuning, instruction tuning, and RLHF/DPO alignment techniques.
  • Four (4) or more years of advanced Python development for machine learning workloads.
  • Strong proficiency with PyTorch and the Hugging Face ecosystem, including Transformers, PEFT, Datasets, and Accelerate.
  • Experience with distributed training frameworks such as DeepSpeed, FSDP, or Megatron.
  • Three (3) or more years of experience with computer vision or multimodal AI models.
  • Understanding of Vision Transformer architectures, including ViT, CLIP, LLaVA, or similar models.
  • Experience processing and augmenting image datasets at scale.
  • Three (3) or more years of experience with AWS machine learning infrastructure, including SageMaker, EC2 GPU instances, and Amazon S3.
  • Experience building machine learning evaluation pipelines, including automated benchmarking, metric computation, and result analysis.
  • Strong software engineering fundamentals, including version control, testing, and CI/CD practices for machine learning workflows.

Why Join Quevera?

Award-Winning Culture

Quevera was recognized as a Top Workplace in the Washington, DC/Baltimore region for 2025, marking our fifth consecutive year receiving this distinction based on employee feedback.

Outstanding Benefits

  • We invest in our employees and their families through a highly competitive benefits package, including:
  • 100% employer-paid medical coverage (optional plan)
  • Competitive options for Medical, Dental and Vision insurance
  • Employer-paid short-term and long-term disability coverage
  • Employer-paid life insurance
  • $5,000 annually for education, training, certifications, and professional development
  • Career advancement through our structured IQWay Program
  • Up to 6% 401(k) match
  • Additional 4% profit-sharing contribution

At Quevera, we believe exceptional people deserve exceptional opportunities. We're more than just a workplace—we're a team of innovators, problem-solvers, and industry experts committed to delivering mission-critical solutions while fostering professional growth, collaboration, and technical excellence.

Quevera is an equal opportunity/affirmative action employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected veteran status, age or any other characteristic protected by law. #LI-AA1