AI​/ML Engineer, Drug Discovery; Contractor

Description

* Note:

this is a 6-month contract position, with possibility of extension. Local candidates based in San Diego are strongly preferred. Remote candidates will also be considered based on qualifications.*

Vividion is a next generation biotechnology company based in San Diego that is leveraging its proprietary chemical proteomics platform to conduct proteome-wide foot printing of drug-protein interactions with unprecedented breadth and precision. Our technology allows us to screen, identify and optimize novel drugs that selectively bind virtually any protein, including proteins previously considered “undruggable”. Our pipeline and emerging programs reflect a matured and productive platform capable of delivering first in class drugs utilizing novel mechanisms of action (allosteric inhibitors, protein-protein interaction inhibitors, functional activators, degraders etc.)

against undruggable targets in the oncology and immunology space.

We prize scientific excellence, creativity, team players and we are committed to continued innovation. We have worked hard to create a collaborative and dynamic work culture where your ideas and discoveries are valued and will have an impact. We are growing and there are opportunities for mentorship and career progression.

Vividion has been recognized as a Top Workplace by The San Diego Union-Tribune from 2022 to 2025.

Vividion is seeking a hands‑on AI/ML Engineer with experience applying data science, machine learning, and informatics approaches to drug discovery. This role is well suited for a collaborative builder who can work directly with scientists, understand scientific questions, and translate complex data into practical models, analytical tools, and reproducible workflows.

The successful candidate will contribute across the full solution lifecycle, including data preparation, exploratory analysis, feature engineering, model development, validation, deployment, and ongoing improvement. The emphasis is on delivering useful, reliable solutions for scientific teams, with opportunities to expand into production AI systems, large language model applications, and agent‑based workflows.

• Partner with research scientists and data stakeholders to define high‑value use cases and translate scientific questions into analytical and machine learning solutions.
• Build, evaluate, and improve predictive models using structured and unstructured scientific data.
• Develop reproducible data pipelines for data ingestion, cleaning, integration, feature generation, and quality control.
• Apply data science, cheminformatics, and related informatics methods to support drug discovery research and decision‑making.
• Perform exploratory data analysis, communicate findings clearly, and recommend appropriate modeling approaches.
• Write maintainable Python and SQL code and contribute to reusable analytical tools, services, and APIs.
• Collaborate with engineering partners to move models and workflows into reliable production or research environments.
• Implement sound practices for experiment tracking, model versioning, testing, documentation, monitoring, and retraining.
• Contribute to AI‑enabled applications, including large language model, Copilot, or agent‑based solutions, when appropriate for the use case.
• Document data sources, assumptions, methods, architectures, experiments, and results for technical and scientific audiences.
• Balance rapid experimentation with scientific rigor, data quality, reproducibility, and operational reliability.

• Bachelor's degree in computer science, data science, mathematics, statistics, computational science, cheminformatics, bioinformatics, or a related…