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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in implementing generative AI solutions and transformer models for Document Understanding tasks, with strong proficiency in Python and familiarity with cloud-based AI/ML services. Capable of evaluating multi-modal models and presenting findings to diverse audiences.
Highest-signal resume keywords
Generative AI & LLMsNatural Language Processing (NLP)Python ProgrammingTransformer ModelsCloud Platforms & AI/ML Services
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Data StructuresDistributed Model TrainingInference OptimizationsNamed Entity RecognitionRelation ExtractionCoreference ResolutionSummarizationKnowledge GraphsOCRHandwriting Recognition
Soft Skills
Presentation SkillsCollaboration
Tools & Technologies
Hugging Face TransformersLangChainLangGraphNLTKGoogle Gemini APIVertex AIAWS EC2S3SageMakerModel Registry
Industry Keywords
Document UnderstandingGenealogical CollectionsHistorical CollectionsZero-Shot LearningFew-Shot Learning
Tech Stack
Tools & technologiesAWSCloudEC2Python
About the role
Key responsibilities & impact- Implement and experiment with cutting-edge transformer and generative AI solutions for Document Understanding tasks
- Work on OCR, handwriting recognition, transcription, Named Entity Recognition, Relation Extraction, Coreference Resolution, Summarization, and Knowledge Graphs
- Process diverse genealogical and historical collections including newspapers, city directories, family history books, and vital records
- Evaluate the performance of multi-modal models in zero-shot and few-shot learning scenarios
- Partner with ML Ops and Data Science Engineers to deploy datasets, truth sets, models, and pipelines for cloud-based training and inference
- Present findings, deliverables, and proposed solutions to technical and non-technical audiences, including teams, stakeholders, and executives
- Build, train, and fine-tune AI models that extract and organize text and image information from historical and genealogical records
- Train, optimize, and deploy models supporting product development, customer success, and content creation across the Family History business
Requirements
What you’ll need- Currently pursuing an advanced degree (Master's or PhD preferred) in Computer Science, Data Science, Statistics, Mathematics, Linguistics, Engineering or related quantitative field with a strong data focus
- Specialization in generative AI & LLMs, embeddings, LoRA, QLoRA, vector databases, transformer models, and Natural Language Processing (NLP)
- Software development expertise including data structures, distributed model training, and inference optimizations
- Strong proficiency in Python and relevant tools and libraries, including transformer models, multi-modal models, and general NLP
- Familiarity with Hugging Face Transformers, agentic frameworks and workflows, LangChain, LangGraph, and NLTK
- Familiarity with cloud platforms and AI/ML services such as Google Gemini API, Vertex AI, AWS EC2, S3, SageMaker, Model Registry, and Bedrock is a plus
- All job offers are contingent on a background check screen that complies with applicable law
Benefits
Comp & perks- Location-flexible work approach: nearest office, home, or hybrid of both, subject to location restrictions and role requirements
- Reasonable accommodations for qualified individuals with disabilities