Senior Life Sciences Knowledge Engineer

Senior Life Sciences Knowledge EngineerAbout us: Why Norstella? Norstella unites market-leading companies that all have a shared goal of improving patient access. Each organization (Evaluate, Citeline, MMIT, Panalgo, The Dedham Group) delivers must-have answers for critical strategic and commercial decision-making.Together, we help our clients:Assess the market need and competitive landscapeKnow precisely which drugs to prioritize in their portfoliosFind out where the launch difficulties will be-before they're difficultiesTrack and improve market access post-launchBy combining the efforts of each organization under Norstella, we can offer an even wider breadth of expertise, cutting-edge data solutions and expert advisory services alongside advanced technologies such as real-world data, machine learning-driven predictive analytics. At Norstella, we don't just deliver information and insights. We deliver answers you can act on.Job DescriptionAbout the role:As a Senior Life Sciences Knowledge Engineer at Norstella, you will sit at the intersection of deep scientific domain expertise and applied AI development. This role will be embedded within a group of life science thought leaders, but will interface across cross-functional teams of data scientists, machine learning engineers and data engineers. Your work centers on curating high-quality fine-tuned datasets which speak to the desired end-to-end behavior we want a model to internalize. The datasets and annotation guidelines/frameworks that govern it will play a critical role in our efforts to deliver predictive analytics and insights across clients.Responsibilities:Translate complex clinical, regulatory, and life sciences subject matter expertise/requirements into repeatable patterns that can be taught to a model through gold standard examples, working closely with data scientists and machine learning engineers to shape the model's schema, vocabulary, and target behavior.Through close collaboration between SME and technical colleagues, develop novel methods and parameters of model behavior, based on interpretation of requirements and quick iteration cycles.Design, build, and continuously refine fine-tuning datasets consisting of input/output pairs that demonstrate desired end-to-end behavior across the target task surface area, edge cases, and known failure modes.Author and maintain the annotation and labeling guidelines that govern dataset construction, ensuring the schema, vocabulary, and definition of "what good output looks like" remain consistent across contributors.Define the task taxonomy and output schema in close partnership with data scientists, ensuring data architecture aligns with downstream evaluation metrics and production requirements across NPD.Train and enable subject matter expert graders running eval rounds, including translating feedback to how data scientists implement improvements at the tool call layer.Run iterative dataset experiments: identify where the model is failing, design targeted example slices to close those gaps, and partner with the human-in-loop SMEs to measure the impact of each dataset change.Maintain provenance, licensing, and compliance documentation for every dataset, ensuring all training data meets GxP, regulatory, and intellectual property standards expected in life sciences and clinical settings.Conduct new proofs of concept for novel domain capabilities.Contribute to Norstella's knowledge base and taxonomy work and help design new agentic workflows based on domain-grounded language models.The guiding principles for success at Norstella:Bold, Passionate, Mission-FirstIntegrity, Truth, RealityKindness, Empathy, GraceResilience, Mettle, PerseveranceHumility, Gratitude, LearningQualifications:Graduate degree in life sciences, medical sciences, computer science or equivalent professional experience.At least 3 years of professional experience in production-grade life science datasets, including with AI-enabled applications.Experience working with structured publishing platforms and data tools; comfort with automation conceptsExperience working with and statistically analysing large and complex data sets, including data cleaning and preprocessing.Experience working with Generative AI, especially LLMs, including agents, throughout the entire software development lifecycle (SDLC).Experience creating MCPs and consuming them into Agentic workflows.Excellent problem-solving skills and the ability to work independently.Excellent communication skills, especially between technical and non-technical teams.Bonus points if you have experience in:Developing, evaluating, deploying, and monitoring algorithms and models from proof-of-concept, experimental stages through production, in a reproducible, auditable, GxP-compliant manner.The AWS ecosystem, specifically with services like S3, ECS, API Gateway, SageMaker, and Bedrock.CI/CD processes, especially as applied to ML operations (MLOps), preferably with Azure DevOps.Experience in fast-paced novel development cycles.Benefits:Medical and prescription drug benefitsHealth savings accounts or flexible spending accountsDental plans and vision benefitsBasic life and AD&D Benefits401k retirement planShort- and Long-Term DisabilityEducation benefitsPaid parental leavePaid time offNorstella is an equal opportunities employer and does not discriminate on the grounds of gender, sexual orientation, marital or civil partner status, pregnancy or maternity, gender reassignment, race, color, nationality, ethnic or national origin, religion or belief, disability or age. Our ethos is to respect and value people's differences, to help everyone achieve more at work as well as in their personal lives so that they feel proud of the part they play in our success. We believe that all decisions about people at work should be based on the individual's abilities, skills, performance and behavior and our business requirements. Norstella operates a zero-tolerance policy to any form of discrimination, abuse, or harassment.