Open Position - Biomedical AI Scientist - Quiver Bioscience Inc - Cambridge, MA

Image; Cambridge (MA); Hybrid; USD 140,000 - 210,000; Full time

Job summary

A tech-driven biotechnology firm in Cambridge, MA seeks a Biomedical AI Scientist to work on their drug discovery platform. The position involves designing AI workflows, building computational pipelines, and collaborating with biologists. Ideal candidates will have a PhD in a relevant field and experience with AI methodologies. Strong programming skills, particularly in PyTorch, are essential. The role requires on-site presence 3-4 days a week, focusing on impactful projects that enhance healthcare solutions.

Qualifications

• PhD in Computer Science, AI, Neuroscience, or related discipline.
• Experience with building LLM systems and RAG workflows.
• Strong proficiency in PyTorch or TensorFlow.
• Experience with image, video, signal processing, or time-series analysis.
• Proficiency in Python, Matlab, Git, SQL, and AWS.
• Experience integrating multi-modal data using knowledge graphs or advanced AI methods.
• High creativity with a passion for neuroscience or biomedical fields.
• Excellent verbal and written communication and leadership.

Responsibilities

• Build computational pipelines for scientific data analysis.
• Design AI workflows integrating optical electrophysiology measurements.
• Collaborate with biologists to optimize validation protocols.
• Construct and manage vector database and knowledge graph infrastructure for rapid similarity search.
• Apply deep learning to extract fingerprints from high‑throughput imaging data for platform foundation.
• Collaborate with wet‑lab biologists to design active learning cycles for validation protocols.
• Lead the software lifecycle for AI products with reproducibility, source control, and documentation.
• Contribute to analytics software development including testing, maintenance, and support.
• Manage timelines and priorities to operate independently and deliver impact.
• Communicate insights to stakeholders and deliver interpretable data products.

Skills

Large Language Models (LLMs)

PyTorch

Image Processing

Machine Learning

Signal Processing

Deep Learning

Interpersonal Skills

Matlab

SQL

AWS

Git

Knowledge graphs

Multimodal fusion

Image processing

Time series

Neuroscience

Communication

Leadership

Education

PhD in relevant field

Tools

Python

Matlab

SQL

AWS

Git

Matlab

Job description

Title of Position: Biomedical AI Scientist

Summary of Position

This AI Scientist will work on computational projects related to Quiver’s drug discovery platform, including helping architect the next generation of our drug discovery intelligence platform. While this role involves foundational work in signal and image processing for our proprietary optical electrophysiology data, there will be a strong focus in expanding this data into a multimodal reasoning engine. The candidate will work on projects integrating complementary data streams (e.g., transcriptomics, high‑content imaging, clinical datasets, etc.) using knowledge graphs, generative AI, and retrieval‑augmented (RAG) methods to answer questions related to human disease and drug discovery. The successful applicant will work as part of a small, close‑knit team at the hub of Quiver’s scientific programs to derive actionable insights from a broad range of relevant biomedical data modalities, including the company’s proprietary all‑optical electrophysiology data and other genomics/omics and imaging data sets. The ideal candidate will be a thoughtful and creative programmer with expertise in artificial intelligence and machine learning and a passion for applying technology to healthcare‑related problems.

Quiver Bioscience is a technology‑driven company established to create transformational medicines for the brain. We combine proprietary single‑cell functional assays with other multi‑modal measurements to discover new biology and new drug targets. We take advantage of cutting‑edge AI/ML to build the world’s most information‑rich maps of neuronal function to drive our drug discovery programs.

This position is based in Cambridge, MA, with the expectation of on‑site presence 3‑4 days per week to support lab integration, team meetings, and collaborative project work. Fully remote applicants will not be considered.

Responsibilities and Duties

• Build computational pipelines for feature engineering and data integration for scientific data analysis.
• Design and build hybrid agentic AI workflows that fuse proprietary optical electrophysiology (oEP) measurements with semantic knowledge from literature and databases.
• Implement and fine‑tune joint embedding models (using techniques like contrastive learning and transformers) to align physiological signals with biological concepts (genes, pathways, and phenotypes).
• Construct and manage vector database and knowledge graph infrastructure required to store, index, and query high‑dimensional biological signatures for rapid similarity search.
• Apply deep learning (e.g., 1D‑CNNs, temporal encoders) to feature‑engineer “fingerprints” from high‑throughput voltage imaging data, serving as the empirical foundation of the platform.
• Collaborate with wet‑lab biologists to design active learning cycles where model predictions automatically suggest and optimize validation protocols (e.g., CRISPR or drug screening).
• Lead the software development lifecycle for AI products, ensuring rigorous standards for reproducibility, source control, performance optimization, and documentation in a Python/PyTorch/Cloud environment.
• Contribute to all aspects of analytics software development including design, implementation, source control, performance optimization, unit testing, defect management, documentation, and ongoing maintenance and support.
• Proficiently manage timelines, relationships, and work priorities to comfortably operate independently to make an impact.
• Utilize excellent interpersonal skills to build consensus, share insights with relevant stakeholders, deliver interpretable data products, and serve both business and scientific goals of the company with your work.

Minimum Qualifications Required

• PhD degree or corresponding demonstrable professional experience in Computer Science, Artificial Intelligence, Neuroscience, Physics, Computer Vision, Electrical Engineering, Mathematics, or related technical discipline (e.g., engineering, science, or biology with a strong quantitative flavor).
• Demonstrated experience building systems with Large Language Models (LLMs), including designing retrieval‑augmented generation (RAG) workflows, semantic search, or agentic workflows.
• Strong proficiency in PyTorch (preferred) or TensorFlow, with specific experience in transformer architectures, graph neural networks (GNNs), or contrastive learning frameworks.
• Experience with image processing, video processing, signal processing, and/or time series analysis.
• Comfort with multiple programming languages and computational APIs (the role will utilize Python, Matlab, git, SQL, and AWS, among others).
• Experience integrating complementary data streams (e.g., transcriptomics, high‑content imaging, clinical datasets, etc.) using knowledge graphs or advanced statistical, machine learning, and AI methods.
• High level of creativity, with a passion for neuroscience or other biomedical fields.
• Excellent skills in the areas of verbal/written communication, problem solving, and leadership.

Additional Qualifications Desired

• Knowledge and experience in biophysics, physiology, or neuroscience, especially electrophysiology, high‑content imaging, or computational neuroscience.
• Experience working with single‑cell data of any modality.
• Comfortable with linear algebra and probability theory.
• Experience with deep‑learning and neural network models, including modern transformer models, unsupervised / self‑supervised learning approaches, data augmentation, and current best‑practices for training and optimization.