Note: The job is a remote job and is open to candidates in USA. Eliassen Group is seeking a Full Stack Clinical Platform Engineer to support Global Development Digital Transformation. The role designs, implements, and operates production-grade Generative AI, machine learning, data engineering, and MLOps solutions for regulated clinical environments while partnering with Clinical Operations, Data Management, Regulatory, and IT.
Responsibilities
- Translate ambiguous clinical and operational problems into well-scoped AI solutions from problem framing and data assessment through prototype, validation, and production deployment
- Design and implement MLOps/LLMOps pipelines to deploy, monitor, and manage large language models in production environments following software engineering best practices
- Collaborate with data scientists to deploy and fine-tune Generative AI models and apply modern techniques from relevant published work where appropriate
- Develop scalable data and ML pipelines for ingestion, preprocessing, validation, training, evaluation, and model deployment across the clinical development ecosystem
- Evaluate and recommend AI tools and frameworks including RAG, vector databases, embedding models, and LLM providers, balancing compliance, performance, and cost
- Develop, deploy, and maintain pipelines for structured and unstructured clinical data, integrating internal systems with CRO and external partner data sources while ensuring data integrity and traceability
- Increase data interoperability and standardization across Global Development systems and other business units to reduce manual effort and accelerate data availability
- Implement automated quality monitoring pipelines for internal and CRO-sourced clinical data, surfacing metrics and triggering corrective workflows aligned with Medical Monitoring Plans
- Ensure compliance with HIPAA, GDPR, and 21 CFR Part 11. Contribute to data governance strategy, data lineage documentation, and audit-readiness
- Maintain code repositories with clean, well-documented, version-controlled code. Uphold engineering best practices including code review, testing, and CI/CD pipelines
Skills
- Advanced degree in computer science, biomedical informatics, statistics, or a related field. MS with 6+ years of relevant experience preferred
- 5–7 years of experience leading data engineering solutions in life sciences or healthcare with end-to-end delivery accountability
- Expertise in clinical or biomedical data infrastructure including data lakes and warehouses optimized for regulatory-grade clinical data
- Experience with modern cloud data platforms such as Snowflake, Databricks, Redshift, or BigQuery. Proficiency in Python, SQL, and R
- Proficiency in cloud architecture on AWS, Azure, or GCP and DevOps practices including CI/CD, containerization with Docker or Kubernetes, and infrastructure-as-code
- Experience building and maintaining pipelines for structured and unstructured data with enterprise integration
- Deep knowledge of HIPAA, GDPR, 21 CFR Part 11, and clinical data standards such as CDISC, HL7, and FHIR
- Hands-on experience with machine learning pipelines and clinical AI/ML applications including NLP, anomaly detection, or predictive modeling
- Strong communication skills to translate technical architectures and outputs into clear recommendations for non-technical stakeholders
- Experience with data governance frameworks, data quality tooling, and metadata management in regulated settings
- Advanced degree in computer science, biomedical informatics, statistics, or a related field. MS with 6+ years of relevant experience preferred
Benefits
- Remote work arrangement
- For our w2 consultants, we offer a great benefits package that includes Medical, Dental, and Vision benefits, 401k with company matching, and life insurance.
Company Overview
Company H1B Sponsorship