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Medical Knowledge Group Jobs in Washington (NOW HIRING)

Group Sales Manager

Washington, DC

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

Medical, Dental and Vision Insurance, 401K * Employee benefit card offering discounted rates in ... knowledge and member enrollments; * Identify and execute key action steps each quarter that will ...

Group Sales Manager

Washington, DC · On-site

$74K - $81K/yr

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

Medical, Dental and Vision Insurance, 401K * Employee benefit card offering discounted rates in ... knowledge and member enrollments; * Identify and execute key action steps each quarter that will ...

Group Sales Manager

Washington, DC · On-site

$74K - $81K/yr

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

Medical, Dental and Vision Insurance, 401K * Employee benefit card offering discounted rates in ... knowledge and member enrollments; * Identify and execute key action steps each quarter that will ...

Senior Medical Coder

Washington, DC · Remote

$24 - $43/hr

  • Retirement

Demonstrate basic knowledge of the impact of coding decisions on revenue cycle * Other duties as ... All employees working remotely will be required to adhere to UnitedHealth Group's Telecommuter ...

Medical Assistant

Rockville, MD

$22 - $25/hr

  • Medical

  • Retirement

  • PTO

Why USA Clinics Group? Founded by physicians with experience at leading academic medical centers ... Apply knowledge of sterile techniques and OSHA regulations. * Train new staff and assist ultrasound ...

Medical Assistant

Rockville, MD · On-site

$22 - $25/hr

  • Medical

  • Retirement

  • PTO

Why USA Clinics Group? Founded by physicians with experience at leading academic medical centers ... Apply knowledge of sterile techniques and OSHA regulations. * Train new staff and assist ultrasound ...

Collections Specialist (Medical)

Bethesda, MD · On-site

$20 - $23/hr

  • Medical

  • Dental

  • Vision

  • Retirement

Addison Group is partnering with our client, a reputable healthcare organization, to identify a ... Working knowledge of EOBs and healthcare billing processes * Excellent communication, organization ...

Be Seen First

Medical Assistant

Fairfax, VA · On-site

$19 - $24/hr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Virginia Pediatric Group, a premier provider of family-centered pediatric care since 1982, is ... Knowledge of physiology and medical terminology is essential for effective communication within the ...

Showing results 21-40

Medical Knowledge Group information

What are the key skills and qualifications needed to thrive at Medical Knowledge Group, and why are they important?

To thrive at Medical Knowledge Group, professionals typically need a background in life sciences, healthcare communications, or pharmaceutical marketing, often supported by relevant degrees. Familiarity with industry-standard tools such as CRM platforms, data analysis software, and reference management systems is valuable. Strong project management, communication, and teamwork skills are essential for delivering complex medical information effectively. These competencies ensure accurate, compliant, and timely solutions for clients in the healthcare and pharmaceutical industries.

How does a Medical Knowledge Group team member typically collaborate with healthcare professionals and clients on projects?

As a team member at Medical Knowledge Group, you will frequently collaborate with healthcare professionals, clients, and internal teams to develop scientific content and communication strategies. This often involves participating in cross-functional meetings, gathering input from medical experts, and ensuring that deliverables meet both scientific accuracy and client expectations. Strong communication and organizational skills are essential, as you'll need to balance multiple projects and adapt to client feedback. This collaborative environment provides valuable exposure to industry leaders and offers opportunities to expand your professional network.

What is Medical Knowledge Group?

Medical Knowledge Group is a company that specializes in providing strategic consulting, medical communications, and data analytics services for clients in the life sciences industry. They work with pharmaceutical, biotechnology, and medical device companies to help them communicate complex scientific information, navigate regulatory requirements, and support product development and commercialization. Their services often include medical writing, publication planning, scientific meetings, and digital engagement solutions. The group employs experts in medicine, science, and communications to ensure accurate and impactful delivery of information.

What is the difference between Medical Knowledge Group vs Medical Writer?

AspectMedical Knowledge GroupMedical Writer
CredentialsTypically requires healthcare or scientific degrees, certifications in medical communicationRequires healthcare, science degrees, and strong writing skills
Work EnvironmentCollaborative teams within healthcare organizations, research institutionsIndividual or team-based writing in pharmaceutical, biotech, or medical publishing companies
Industry UsageUsed in medical education, research, and healthcare communicationUsed in creating clinical trial reports, regulatory documents, and educational materials

The Medical Knowledge Group focuses on collaborative healthcare and research communication, often involving team-based efforts. Medical Writers primarily produce written content such as reports and regulatory documents. While both roles require medical knowledge and communication skills, the Medical Knowledge Group emphasizes team collaboration and strategic communication, whereas Medical Writers concentrate on producing precise, compliant documentation.

What cities in Washington are hiring for Medical Knowledge Group jobs?

Cities in Washington with the most Medical Knowledge Group job openings:

Infographic showing various Medical Knowledge Group job openings in Washington as of August 2026, with employment types broken down into 1% As Needed, 77% Full Time, 17% Part Time, and 5% Contract. Highlights an 96% Physical, 1% Hybrid, and 3% Remote job distribution.

Principal Knowledge & Data Architect

Howard Hughes Medical Institute (HHMI)

Chevy Chase, MD • On-site

Full-time

Medical, Retirement

Re-posted 8 days ago


Job description

Primary Work Address: 4000 Jones Bridge Road, Chevy Chase, MD, 20815
Current HHMI Employees, click here to apply via your Workday account.
HHMI is focused on supporting and moving science forward in a variety of different ways ranging from conducting basic biomedical research, empowering educators, inspiring students, developing the next generation of scientists - even stretching into film and media production. Our Headquarters is in the greater Washington, DC metro area and is home to over 300 employees with expertise in investments, communications, digital production, biomedical sciences, and everything in between. The work housed here supports and augments the groundbreaking research conducted in HHMI labs across the nation. As HHMI scientists continue to push boundaries in laboratories and classrooms, you can be sure that your contributions while working here are making a difference.
The EverydayAI Accelerator exists to turn generative AI into daily reality across HHMI's administrative and operational functions. This role owns HHMI's knowledge management layer for AI: the discipline of turning institutional information (documents, records, policies, scientific content, operational data) into structured, retrievable, trustworthy knowledge that AI systems can actually use.
The work is technical and grounded. You will design and operate the retrieval-augmented generation pipelines that every Accelerator project depends on: the chunking, embedding, indexing, and retrieval patterns that turn HHMI's content into something AI can find and reason over. For use cases where a graph representation is the right tool (complex entity relationships, lineage, multi-hop reasoning), the knowledge graph gets built and operated alongside it. This work happens in partnership with the Principal AI Architect, who owns the AI platform and engineering foundation, and the Technology and Systems Management (TSM) Data Integrations team, who owns the data pipelines from source systems. Whoever holds this role designs the knowledge architecture and is accountable for operating it.
Why this role matters
HHMI's scientific, financial, and operational knowledge lives scattered across documents, databases, and systems never built to talk to AI. Without someone accountable for turning that information into something structured and trustworthy, every AI initiative at HHMI either repeats the same expensive groundwork or surfaces answers no one can stand behind. This role solves that problem once so that every Accelerator project and future AI effort can build on a governed, reliable knowledge foundation instead of reinventing it.
What you will actually do
  • Own HHMI's knowledge management architecture. Design how institutional content is captured, structured, classified, retrieved, and maintained over time. Make the calls on representation (chunked text, embeddings, structured records, knowledge graphs, or hybrid) for each kind of content and each kind of use case, and own the consequences.

  • Build and operate the RAG pipelines. Design and run the retrieval-augmented generation systems that every AI product at HHMI consumes, including document processing, chunking, embedding, indexing, hybrid retrieval, re-ranking, query rewriting. New projects inherit proven patterns; they do not roll their own.

  • Build knowledge graphs where the use case requires it. For problems where graph representation is the right tool (complex entity resolution, multi-hop reasoning, lineage and provenance, relationship-heavy queries), design the data model, stand up the graph store, and operate it.

  • Extract structure from unstructured content. Build the pipelines that turn HHMI's documents (policies, applications, financial records, scientific content) into something AI can consume. Use the right mix of LLM-based extraction, classical NLP, and rule-based methods for each source, and be able to explain why.

  • Solve entity resolution. The same person, fund, application, or concept appears across many systems with many representations. Build the deduplication, linking, and canonicalization that lets the institution rely on a single, defensible truth.

  • Govern knowledge classification and lineage. Sit in the AI governance group as the technical voice on knowledge sensitivity, provenance, and retention.

  • Partner with Data Integrations and the AI platform team. TSM Data Integrations owns the plumbing across HHMI's source systems, and you define what AI needs from it while co-building the contracts that connect the two layers. The Principal AI Architect owns the AI platform; the knowledge layer it reasons over comes from this seat.

  • Communicate across the altitude range. Translate knowledge-architecture trade-offs for engineering teams, then turn around and explain the same decisions to a business leader or executive in terms that actually land. Expect to do both regularly.

What we are looking for
  • Real production RAG experience. Proven experience shipping retrieval-augmented systems and running in production, with failures debugged back through the pipeline and the broken step rebuilt. Hybrid retrieval, chunking strategy, query understanding, and re-ranking used as working tools, not just concepts. This is the core of the role.

  • Knowledge management and data modeling. A librarian's instinct for content (what's authoritative, what's stale, who can see it), plus the ability to look at an unfamiliar domain and identify the right entities, relationships, and representation, defending why an attribute is a node, an edge, or not modeled at all.

  • Knowledge graph and entity resolution experience. At least one knowledge graph designed, built, and operated in production, with a clear sense of when a graph beats a vector store or document chunk. Deduplication and linking problems solved where the same thing has seven names across four systems and none of them are wrong.

  • Information extraction and production rigor. Extraction pipelines built to turn unstructured text into structured knowledge using a mix of LLMs, classical NLP, and rule-based methods, treating embedding versioning, retrieval evaluation, corpus drift, and re-indexing as first-class engineering concerns. "The model gave the wrong answer" is a debuggable system, not a shrug.

  • Data engineering, security, and range. Fluency in a data integration team's tools (SQL, Databricks, dbt, ETL patterns) pairs with designing around data classification, access controls, and PII handling from the first conversation rather than as a final review. Ability to lead engineers technically without a reporting line, and to explain the same decision to a non-technical stakeholder in terms that help them choose.

  • Technical range to operate at this level. Strong proficiency in Python and SQL. Production experience with vector databases (Postgres pgvector, Pinecone, Weaviate, Qdrant, or comparable) and embedding pipelines. Production experience with at least one graph database (Neo4j, AWS Neptune, JanusGraph, TigerGraph, Stardog, or comparable) and graph query languages (Cypher, SPARQL, or Gremlin). Working knowledge of modern NLP and information extraction. Fluency in the modern data stack (Databricks, dbt, or comparable).

  • Education and experience. Bachelor's degree or equivalent, plus at least eight years of hands-on experience across data engineering, information retrieval, and applied machine learning, with at least three years focused on production knowledge management for AI systems (retrieval-augmented generation, knowledge graphs, or both).

Nice to have
  • Background in library or information science, formal ontology, or semantic web technologies (RDFS, OWL, SKOS).

  • Experience with hybrid retrieval (graph + vector) and GraphRAG patterns.

  • Familiarity with MCP, structured-output patterns, and AI agent tool design.

  • Experience with master data management, data catalogs, or lineage tooling at enterprise scale.

  • Prior experience in research, academic, or mission-driven institutional environments.

What this role is not
  • A data engineering role. This role partners with TSM's Data Integrations team on source-system pipelines and the data warehouse, but doesn't own that plumbing; it owns the knowledge layer that sits on top of it.

  • An AI platform or AI infrastructure role. The Principal AI Architect owns the AI engineering foundation, the platform services, the reference architectures, and the production deployment patterns. Your job is to ensure there is structured, retrievable, trustworthy knowledge for that platform to reason over.

  • A pure research role. Staying current on the field (RAG, knowledge representation, GraphRAG, neuro-symbolic methods) matters, but the work is building and operating production knowledge systems, not publishing about them.

  • A role for someone whose RAG or graph experience is only academic or prototype-scale. You need production scars: systems that have handled real users, real failure modes, and real corpus evolution over time.

Practical details
This role is hybrid, with 3 days per week in-person at HHMI's offices in Chevy Chase, MD. It reports to the Director, AI Enablement.
We encourage qualified candidates who are eligible to work in the United States to apply. Please note, we are not able to sponsor a visa for this position at this time.
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Compensation and Benefits
Our employees are compensated from a total rewards perspective in many ways for their contributions to our mission, including competitive pay, exceptional health benefits, retirement plans, time off, and a range of recognition and wellness programs. Visit our Benefits at HHMI site to learn more.
Hiring Pay Range
$174,770.40 - $218,463.00
Pay Type:
Annual
The posted range reflects HHMI's good faith estimate of the anticipated hiring salary range for this role at the time of posting. Actual hiring compensation is determined by a candidate's qualifications, experience, and internal equity.
HHMI is an Equal Opportunity Employer
We use E-Verify to confirm the identity and employment eligibility of all new hires.