Note: The job is a remote job and is open to candidates in USA. Bayside Solutions is seeking a contract AI/ML Scientist to build scientific data ingestion and management systems supporting AI agents and downstream analytics. The role focuses on creating traceable, validated data products and reusable workflows, initially for structuring CRO reports related to TCI synthetic chemistry.
Responsibilities
- Build and maintain ingestion and extraction pipelines for documents, tables, images, and structured scientific datasets
- Implement data representations and typed schemas that support agent tasks and analytical requirements defined by team scientists
- Preserve source evidence and provenance; manage identifier canonicalization, missingness, conflicting values, and data lineage
- Implement automated data QC and deterministic validation checks that identify errors and route uncertain records for review
- Build reproducible pipelines into Databricks, with versioned data products and documented transformations and assumptions
- Work with scientists to develop and maintain benchmark datasets and evaluation tooling for source-grounded assessments by scientists and external collaborators
- Partner with platform engineers on interfaces, failure recovery, repository maintenance, and deployment preparation
- Communicate data limitations and progress, incorporate feedback, and adapt reusable pipelines to AP-MS, DEL, and other needs
Skills
- Degree in computer science, data science, engineering, quantitative science, or a related field, or equivalent practical experience
- Strong Python and SQL skills, including agentic coding tools, with experience designing and maintaining data ingestion, transformation, and management pipelines
- Experience with APIs, typed schemas, automated testing, debugging, and reproducible computational workflows
- Experience managing data quality, provenance, missingness, and consistent identifiers across heterogeneous sources
- Experience with Git-based development, code review, packaging, documentation, and secure handling of internal data
- Basic fluency in machine learning data requirements, with enough chemistry and biology understanding to follow scientific use cases
- Ability to communicate uncertainty and data limitations clearly to colleagues with different scientific and software backgrounds
- Ability to independently execute defined work, meet agreed milestones, incorporate feedback, and collaborate across engineering roles
- Experience with document processing, OCR, or extraction from text, tables, and images, including multimodal model applications
- Experience with Databricks, cloud storage, scalable data processing, or workflow orchestration
- Experience managing scientific datasets in drug discovery, cheminformatics, bioinformatics, or related research
- Experience building benchmark datasets, evaluation infrastructure, or source-grounded validation of extracted information
- Experience using AI-assisted coding tools with code review and testing, or delivering projects in biotechnology or consulting
Benefits
- Remote role
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