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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates extensive experience in Python production at scale, with a strong background in NLP techniques including LLMs, embeddings, and classification. Capable of managing high-volume workloads and collaborating effectively with cross-functional teams to drive product decisions and outcomes.
Highest-signal resume keywords
Deep Python Production ExperienceStrong NLP BackgroundExperience Building EvaluationsFamiliarity with AWSExposure to Agentic AI Applications
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, selecting approaches based on evaluation, cost, and operational tradeoffs
- Build golden evaluation sets with SMEs and vendors, select metrics, and balance speed, quality, and cost
- Write production-quality Python and manage concurrency and cost for high-volume LLM workloads
- Structure extensible code that engineers can ship and data scientists can maintain
- Collaborate with data engineers using Airflow and Dagster to orchestrate reliable, idempotent, retryable, evaluable pipeline stages
- Contribute to agentic AI applications that reason over the enriched scientific corpus
- Work with editors, product managers, and engineers to inform product decisions and translate stakeholder feedback into modeling work
- Own domain-specific content modeling end to end, from evaluation sets through production deployment
- Own models, evaluations, shipped changes, and production outcomes
Requirements
What you’ll need- Deep Python production experience at scale for years
- Knowledge of asyncio, threads, and queues, including tradeoffs
- Strong NLP background across LLMs, transformers, embeddings, retrieval, NER, classification, and sequence labeling
- Experience building evaluations and learning from results
- Ability to compare modeling approaches using evaluations, cost estimates, and operational tradeoffs
- Track record of shipping production systems that deliver value to real users
- Experience working with scientific or scholarly text preferred
- Familiarity with AWS (S3, Batch, Lambda, SageMaker) and Parquet or Iceberg data lake patterns preferred
- Experience running LLMs under production cost and latency budgets preferred
- Exposure to agentic AI applications, including tool use, multi-step reasoning, guardrails, and trajectory evaluation preferred
- Resume/CV required when applying
Benefits
Comp & perks- Meeting-free Friday afternoons
- Professional development opportunities
- Employee programs supporting community, learning, and growth
- Comprehensive benefits package
- Competitive compensation
- Reasonable accommodation for applicants and employees 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
NLPLLMsTransformersEmbeddingsNERClassificationSequence LabelingAsyncioProduction SystemsEvaluation Metrics
Tools & Technologies
AirflowDagsterAWS S3AWS BatchAWS LambdaAWS SageMakerParquetIceberg
Industry Keywords
Scientific TextScholarly TextCost EstimatesOperational TradeoffsAgentic AI Applications