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Rlhf Jobs in Silver Spring, MD (NOW HIRING)

LLM Specialist

Columbia, MD ยท 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 ...

LLM Specialist

Columbia, MD ยท On-site +1

$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 ...

AI Integration Engineer

Washington, DC ยท On-site

$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 ...

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 ...

Applied AI Engineer

Arlington, VA ยท On-site

$159K - $263K/yr

You have hands-on experience with LLM post-training methods (e.g., continued pre-training, SFT, RLHF, DPO, PPO, GRPO). * You have experience curating, cleaning, and preprocessing datasets for ...

... RLHF. * An engineering mindset as shown by a track record of delivering models at scale both in terms of training data and inference volumes. * Experience in delivering libraries, platform level code ...

... RLHF. * An engineering mindset as shown by a track record of delivering models at scale both in terms of training data and inference volumes. * Experience in delivering libraries, platform level code ...

... RLHF. * An engineering mindset as shown by a track record of delivering models at scale both in terms of training data and inference volumes. * Experience in delivering libraries, platform level code ...

... RLHF. * An engineering mindset as shown by a track record of delivering models at scale both in terms of training data and inference volumes. * Experience in delivering libraries, platform level code ...

Showing results 21-40

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:

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.

LLM Specialist

eSimplicity

Columbia, MD โ€ข On-site

$93K - $100K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 5 days ago


Job description

Description:

About Us:

eSimplicity is a modern digital services company that partners with government agencies to improve the lives and protect the well-being of all Americans, from veterans and service members to children, families, and seniors. Our engineers, designers, and strategists cut through complexity to create intuitive products and services that equip federal agencies with solutions to courageously transform today for a better tomorrow.


Responsibilities:

The LLM Specialist will drive the design, development, and operationalization of advanced large-language-model capabilities across a cloud-based analytics ecosystem. This role leads innovation efforts around cutting-edge AI, owning the architecture and strategy for fine-tuning, retrieval-augmented generation (RAG), agentic frameworks, and domain-specific model adaptation. The specialist will guide the development of high-impact prototypes, oversee the evolution of scalable LLM pipelines, and ensure robust governance, security, and performance across all model implementations. Partnering with engineering, product, and data teams, this position provides technical leadership, evaluates emerging LLM technologies, sets best practices, and helps drive transformation through the practical, safe, and effective deployment of generative AI.

Requirements:

Required Qualifications:

  • All candidates must pass public trust clearance through the U.S. Federal Government. This requires candidates to either be U.S. citizens or pass clearance through the Foreign National Government System which will require that candidates have lived within the United States for at least 3 out of the previous 5 years, have a valid and non-expired passport from their country of birth and appropriate VISA/work permit documentation.
  • Bachelor’s Degree and 5+ years of previous systems engineering experience.
  • Experience developing and working with large language models (LLMs), transformer-based architectures, and generative AI solutions.
  • Experience fine-tuning LLMs, applying parameter-efficient training methods (e.g., LoRA, PEFT), and developing effective prompt engineering strategies.
  • Experience designing, implementing, and optimizing Retrieval-Augmented Generation (RAG) solutions, including embeddings, retrieval workflows, vector databases, and search optimization.
  • Hands-on experience with LLM development frameworks and orchestration tools such as LangChain, LlamaIndex, or similar technologies.
  • Strong Python programming skills with experience building, testing, and deploying AI/ML applications.
  • Experience working with distributed computing environments, GPU-accelerated workloads, or large-scale model training and inference.
  • Experience designing, deploying, and supporting AI/ML solutions in cloud environments such as Microsoft Azure, Amazon Web Services (AWS), Google Cloud Platform (GCP), or similar platforms.
  • Knowledge of MLOps and LLMOps practices, including source control, CI/CD pipelines, automated testing, monitoring, performance optimization, and model governance.
  • Ability to lead technical discussions, collaborate effectively with cross-functional teams, mentor team members, and communicate complex technical concepts to both technical and non-technical audiences.

Desired Qualifications:

  • Experience implementing multi-agent or agentic AI systems for task automation and reasoning.
  • 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 hybrid search, graph retrieval, or long-context optimization.
  • Experience optimizing model inference through quantization, model compression, or model distillation.
  • Background integrating LLM services with large-scale analytics environments (e.g., Databricks, Snowflake, Spark).
  • Strong skills in exploratory data analysis, feature engineering, and data modeling to support domain-specific LLM customization.
  • Experience developing innovative prototypes or POCs that leverage state-of-the-art generative AI approaches.
  • Exposure to emerging architectures such as mixture-of-experts models, long-context transformers, or experimental generative frameworks.


Working Environment:
eSimplicity supports a remote work environment operating within the Eastern time zone so we can work with and respond to our government clients. Expected hours are 9:00 AM to 5:00 PM Eastern unless otherwise directed by manager.


Occasional travel for training and project meetings. It is estimated to be less than 5% per year.


Benefits:
eSimplicity offers a comprehensive benefits package, including medical, dental, and vision coverage, 401(k) retirement benefits, paid time off, paid holidays, life and disability insurance, and additional wellness and employee support programs. Eligibility may vary based on employment status and applicable plan terms.


Reasonable Accommodation:
eSimplicity is committed to providing reasonable accommodations to qualified individuals with disabilities during the application and hiring process. Applicants who need assistance or an accommodation should contact Human Resources.

Equal Employment Opportunity:
eSimplicity is an Equal Opportunity Employer, including disability and protected veteran status. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, protected veteran status, disability, or any other legally protected status.