Principal Scientist, AI - Remote (United States)

Rancho BioSciences LLC • Boston, MA

14d • Remote

About The Position

As we continue to grow, Rancho BioSciences is seeking a Principal Scientist to define and deliver AI-enabled data products and solutions that transform how our clients generate insights across discovery, development, and real-world evidence (RWE). This role is a hands-on technical leadership position for someone who can shape use cases, architect solutions, build prototypes, and guide production deployments-while serving as a trusted advisor to clients and a mentor to internal teams.
Who We Are
Rancho BioSciences is a San Diego-based provider of biomedical data curation and data science services for pharma and biotech, spanning drug discovery through translational research. Our teams of scientists, data engineers, and software experts deliver end-to-end solutions across data curation, management, mining, and analysis to help customers accelerate R&D. We partner long-term with blue-chip clients and emerging biotechs, bringing scientific rigor, quality, and a customer-first mindset to every engagement.

Requirements

• PhD in Computational Biology, Bioinformatics, Computer Science, Statistics, or related field (or comparable demonstrated relevant experience).
• 5+ years delivering ML/AI solutions in life sciences (discovery, translational, clinical, or RWE), including 3+ years leading cross-functional technical teams.
• Hands-on expertise with Python and core ML/DL frameworks (PyTorch and/or TensorFlow; Keras); strong software engineering practices (testing, code review, version control).
• Proven experience building production-grade data and deployment pipelines: SQL and Spark, containerization (Docker), orchestration (Airflow/Prefect), cloud services (AWS preferred; Azure/GCP welcome).
• Experience with multi-agent systems and agent orchestration in production use cases.
• Track record of rigorous LLM evaluation: designing task-specific benchmarks, implementing automated evaluation frameworks, diagnosing failure modes, and iteratively optimizing retrieval and generation pipelines for accuracy, latency, and cost.
• Practical GenAI/LLM experience: retrieval-augmented generation, vector databases (e.g., FAISS, Milvus, pgvector), prompt engineering, evaluation frameworks, and safety/guardrail techniques.
• Strong client-facing skills: translating scientific needs into technical solutions, presenting to senior stakeholders, and contributing to scope and SOWs.
• Domain fluency with clinical, preclinical, or RWE data and relevant standards (CDISC, OMOP, FHIR) and biomedical ontologies (e.g., OBO, SNOMED, MeSH).

Nice To Haves

• Experience with knowledge graphs (RDF/OWL, SPARQL, Neo4j) and entity/relationship modeling.
• Biomedical NLP (e.g., BioBERT, SciBERT) and ontology-driven text mining.
• Privacy and compliance expertise: de-identification, data use agreements, and audit readiness.
• Familiarity with data product thinking and monetization of curated datasets.
• Familiarity with multimodal foundation models in biomedical domains: single-cell embeddings (e.g., scGPT, Geneformer), molecular/chemical LLMs (e.g., ChemBERTa, MolBERT), or medical imaging models (e.g., BiomedCLIP, pathology foundation models).
• MLOps proficiency with platforms such as AWS SageMaker, Vertex AI, or Kubeflow; experiment tracking (MLflow/Weights & Biases); model registry and monitoring.

Responsibilities

• Partner with clients to identify high-value AI/ML and GenAI use cases; lead discovery workshops and author clear requirements, system designs, and reference architectures.
• Lead the design and delivery of end-to-end solutions: data ingestion and governance, feature engineering, model development, LLM/RAG pipelines, evaluation, deployment, and lifecycle management.
• Help maintain best practices for safe, effective GenAI: prompt strategies, retrieval design, vector stores, guardrails, bias/toxicity checks, privacy/PII handling, and human-in-the-loop review.
• Build internal accelerators and reusable assets: ontologies/knowledge graphs, data models, feature stores, evaluation tools, and workflow templates that improve delivery speed and quality.
• Guide build-buy-partner decisions; evaluate vendors and open-source components; create objective comparison criteria and recommendations.
• Collaborate with Sales/Account Management on pre-sales: scope use cases, design pilots/POCs, estimate level of effort, and contribute to statements of work.
• Provide scientific and technical leadership to project teams; mentor early-career scientists and engineers; model Rancho's values of scientific rigor, humility, and customer focus.
• Proactively identify opportunities to apply emerging AI/ML capabilities to client challenges and internal processes, evaluating new approaches with a critical eye toward measurable value.
• Stay current with the rapidly evolving AI/ML landscape: monitor research, evaluate new tools and frameworks, and translate relevant advances into actionable recommendations for clients and delivery teams.
• Contribute to Rancho's thought leadership through papers, talks, and client education.

Benefits

• Great opportunities to grow and develop with the company as we scale
• Competitive base salary
• Fully Remote environment - work from anywhere!
• Flexible work arrangements
• Great company swag
• Private medical coverage and/or personal stipend, to ensure you and your family's wellbeing
• Participation in country-specific financial empowerment programs (401k, Pension/Retirement, FSA/HSA, etc.)

What This Job Offers

• Job Type: Full-time
• Career Level: Principal
• Education Level: Ph.D. or professional degree