• Innovate and improve the machine learning models to enable financial progress for customers • Design, develop, and deploy machine learning models to solve practical problems • Partner with business leaders and technical experts to develop new data sources and improve modeling methodology

Role Description This Role is Perfect for You If You Love: - A high-energy start-up working with a brilliant and passionate team - Working on problems that make a real difference in people’s lives - Understanding and delivering on reliable and well-characterized products and deliverables within a highly innovative and fast-changing environment: clinical data extraction and aggregation, the relation between data processing and QA framework; LLM tuning and training, pedantic data curation, compute architecture, data exchange. - Rockstar teammates: you will be working with a strong team with decades of prior work experience in artificial intelligence, software systems, molecular biology, and clinical medicine - Innovation and problem solving to provide order-of-magnitude improvements in capabilities for data handling and analysis while maintaining traceable data and methods development We are hiring an AI Curation Data Scientist who will, using traditional computing and custom AI model training, work on mission-critical projects driven by xCure’s product development needs and will expand xCures’ complex, innovative health data processing, extraction, and analysis capabilities. We’re looking for an individual who values team-building, cooperation, and communications with colleagues to serve the needs of our customers. You will reach out across the organization for guidance on engineering, clinical, PHI/PII, data policy, and business topics as needed. Projects will include significant data processing challenges, such as C-CDA XML parsing and de-identification of structured and unstructured EHR content. Equally important projects will address data curation and custom AI model training. You will author software and AI models and take the lead on data set curation. You will serve as the anchor of Data Science data set quality assurance within an innovative, fast-moving team. Team responsibilities are key requirements for this position, which will deliver large and complex data products and data analysis tools. Qualifications - Ph.D., or equivalent experience in Computer Science, Software Engineering, Statistics, Biology, or related field - Minimum of 10 years of hands-on experience in data science, machine learning, AI, data analysis, software development, and/or predictive analytics - Expertise in generative AI and transformer models, especially training of LLMs - Significant prior experience with curating data sets to train LLMs - Significant hands-on coding experience with LLMs, embeddings models, sentence_transformers, and authoring python code to build data extraction and/or classification tools - Significant prior work experience with parsing XML, JSON, and/or other complex data formats, preferably C-CDA health data - Experience with TensorFlow, PyTorch, and/or scikit-learn - Software development skills including git - Proven efficiency using, and cautious approach to using, LLM-assisted coding - Experience writing unit and integration tests for scientific/clinical data software as well as with developing scientifically motivated data quality assessments - Experience as a senior technology development leader, contributing while coordinating the work of colleagues - Flexible, innovative, can-do approach to delivering software and data products balanced with team cooperation - A passion for successful delivery of team work products Requirements - Extensive experience with data handling efficiency tools, such as jq, xq, Unix command-line tools such as sed, bash programming - Deep understanding of regex - Extensive AWS experience and understanding of tradeoffs for different types of data storage for AI training - Significant prior experience with PHI and PII, HIPAA, and de-identification is a major plus - Software development experience in multiple coding languages - Confidence extending the capabilities of open source tools - Experience with multiple approaches to LLM-assisted coding, such as within Visual Studio, copilot, Claude Code; and familiarity with frontier and open model capabilities - Experience with remote teams and solving technical project communications challenges Benefits - Base salary range: $150,000 to $200,000 annually - Medical, Dental, Vision insurance - 401k - Equity options

Role Description This is a senior, hands-on technical leadership role for someone who can design, build, and scale end-to-end GenAI systems — from architecture decisions to production deployment. - Lead LLM-based solution design (RAG, agents, fine-tuning strategies) - Build end-to-end GenAI applications (data retrieval orchestration APIs UI) - Own critical architectural decisions (model selection, vector DBs, pipelines) - Implement AI governance, safety, and compliance layers (PII, guardrails, monitoring) - Mentor engineers and drive AI best practices across teams Qualifications - 6+ years in Data Science / AI Engineering - 4+ years building production-ready Python systems - 2+ years delivering real-world LLM / GenAI applications - Proven experience with RAG pipelines (design + optimization) - Strong understanding of LLM trade-offs (RAG vs fine-tuning vs hybrid) - Experience making architecture-level decisions - Fluent English & strong stakeholder communication Requirements - Experience with LlamaIndex / LangGraph - Exposure to multimodal models - Experience with Azure cloud ecosystem - Ability to build lightweight UIs / demos for AI systems - Mentoring junior & mid-level engineers Benefits - Direct ownership of enterprise-scale GenAI systems - Opportunity to shape AI architecture decisions end-to-end - Exposure to global clients across multiple industries - Strong learning ecosystem (110+ trainings/year + Udemy access) - Clear path toward technical leadership and influence

Role Description This is a senior, hands-on technical leadership role for someone who can design, build, and scale end-to-end GenAI systems — from architecture decisions to production deployment. - Lead LLM-based solution design (RAG, agents, fine-tuning strategies) - Build end-to-end GenAI applications (data retrieval orchestration APIs UI) - Own critical architectural decisions (model selection, vector DBs, pipelines) - Implement AI governance, safety, and compliance layers (PII, guardrails, monitoring) - Mentor engineers and drive AI best practices across teams Qualifications - 6+ years in Data Science / AI Engineering - 4+ years building production-ready Python systems - 2+ years delivering real-world LLM / GenAI applications - Proven experience with RAG pipelines (design + optimization) - Strong understanding of LLM trade-offs (RAG vs fine-tuning vs hybrid) - Experience making architecture-level decisions - Fluent English & strong stakeholder communication Requirements - Experience with LlamaIndex / LangGraph - Exposure to multimodal models - Experience with Azure cloud ecosystem - Ability to build lightweight UIs / demos for AI systems - Mentoring junior & mid-level engineers Benefits - Direct ownership of enterprise-scale GenAI systems - Opportunity to shape AI architecture decisions end-to-end - Exposure to global clients across multiple industries - Strong learning ecosystem (110+ trainings/year + Udemy access) - Clear path toward technical leadership and influence