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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in Natural Language Processing (NLP) with a focus on modern and classical approaches, including LLMs, transformers, and entity recognition. Capable of building evaluation metrics and pipelines while collaborating effectively with cross-functional teams to enhance scientific applications.
Highest-signal resume keywords
Natural Language Processing (NLP)LLMs And TransformersPython ProgrammingEvaluation Metrics DevelopmentAWS Familiarity
Tech Stack
Tools & technologiesAbout the role
Key responsibilities & impact- Design and build NLP enrichment pipelines extracting entities, classifications, claims, and summaries from scientific full text at scale
- Compare traditional NLP, embedding-based retrieval, LLM prompting, and fine-tuned smaller models
- Select approaches based on evaluation, cost, and operational tradeoffs
- Build golden evaluation sets in consultation with SMEs and vendors
- Choose evaluation metrics and balance speed, quality, and cost
- Contribute to agentic AI applications that reason over enriched scientific corpora
- Help agents ground and defend their answers
- Work directly with editors, product managers, and engineers
- Bring modeling perspectives into product decisions
- Translate stakeholder feedback into concrete modeling work
- Own models, evaluations, code, production changes, and outcomes end to end
Requirements
What you’ll need- Strong NLP background across modern approaches including LLMs, transformers, embeddings, and retrieval
- Strong NLP background across classical approaches including NER, classification, and sequence labeling
- Experience building evaluations and learning from results
- Clean Python code
- Comfort working in exploratory notebooks and production repositories
- Ability to compare modeling approaches and select the appropriate approach based on evaluation, cost, and operational tradeoffs
- Preferred: Experience working with scientific or scholarly text
- Preferred: Familiarity with AWS, including S3, Batch, Lambda, and SageMaker
- Preferred: Familiarity with Parquet or Iceberg data lake patterns
- Preferred: Experience running LLMs under real cost and latency budgets in production
- Preferred: Exposure to agentic AI applications, including tool use, multi-step reasoning, guardrails, and trajectory evaluation
- Resume/CV required when applying
Benefits
Comp & perks- Meeting-free Friday afternoons for heads-down work and professional development
- Professional development opportunities
- Employee programs supporting community, learning, and growth
- Comprehensive benefits package
- Reasonable accommodation for applicants with disabilities
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Entity Recognition (NER)ClassificationSequence LabelingEmbedding-Based RetrievalModel ComparisonEvaluation BuildingCost AnalysisOperational TradeoffsData Lake PatternsAgentic AI Applications
Soft Skills
CollaborationStakeholder CommunicationFeedback Translation
Tools & Technologies
AWS S3AWS BatchAWS LambdaAWS SageMakerExploratory NotebooksProduction Repositories
Industry Keywords
Scientific TextScholarly TextModeling PerspectivesGolden Evaluation SetsMulti-Step Reasoning