Machine Learning Research Scientist, Interpretability

New York, New York, United States

Auto‑apply with AI Apply

Not SpecifiedCompensation

Junior (1 to 2 years), Mid-level (3 to 4 years)Experience Level

Full TimeJob Type

UnknownVisa

Artificial Intelligence, BiotechnologyIndustries

Requirements

Candidates should possess a Bachelor's degree in Computer Science, Computer Engineering, Mathematics, Physics, or a related technical field, and a PhD with 2 years of research experience, or a Bachelor's degree with 4+ years of research or industry experience in Deep Learning, Artificial Intelligence, or other relevant fields. Strong proficiency in Python and expertise in at least one major deep learning framework such as PyTorch, TensorFlow, or JAX is required, along with a publication record in top-tier AI conferences or journals like NeurIPS, ICML, or ICLR.

Responsibilities

As a Machine Learning Research Scientist, Interpretability, you will develop specialized methods for understanding biological reasoning models, reverse-engineering how they represent and process complex biological information, and design and conduct experiments to uncover interpretable features across biological scales. You will address unique challenges in biological model interpretation, such as disentangling the multi-scale, hierarchical representations of biological systems, and build biology-specific visualization tools that can map model activations to meaningful biological concepts, working alongside founders and team members to build AI systems capable of processing and reasoning across multiple biological data modalities simultaneously.

Skills

Python

PyTorch

TensorFlow

JAX

Deep Learning

Biological Modeling

Feature Engineering

Visualization

Machine Learning

Interpretability

Output Biosciences

Develops preventative therapies for chronic diseases

About Output Biosciences

Output Biosciences focuses on developing preventative therapies aimed at extending human healthspan by addressing chronic diseases such as diabetes and heart disease. The company combines biotechnology with artificial intelligence to create therapies that can be discovered and manufactured more quickly and safely than traditional methods. This allows them to bring new treatments to market in just a few months, which is much faster than the usual drug development process. Their main clients include healthcare providers, pharmaceutical companies, and research institutions seeking effective solutions for chronic disease management. Output Biosciences differentiates itself by leveraging computational biology to streamline therapy development and commercialization, generating revenue through partnerships and licensing. The goal of Output Biosciences is to fundamentally change healthcare by preventing chronic diseases before they occur.

New York City, New YorkHeadquarters

2020Year Founded

$125KTotal Funding

PRE_SEEDCompany Stage

AI & Machine Learning, Biotechnology, HealthcareIndustries

1-10Employees

Risks

Increased competition from AI-driven biotech startups threatens market share.

Regulatory scrutiny on AI applications may delay approval processes.

Rapid technological advancements may render current methods obsolete without continuous innovation.

Differentiation

Output Biosciences integrates AI and computational biology for rapid therapy development.

The company focuses on preventative therapeutics to extend human healthspan.

Output Biosciences accelerates drug development timelines, bringing therapies to market in months.

Upsides

Growing interest in AI-driven drug discovery boosts investment and partnerships.

Rise of personalized medicine creates opportunities for tailored AI-integrated therapies.

FDA's acceptance of AI-driven drug development enables faster regulatory pathways.

Land your dream remote job 3x faster with AI

Try Jobo Free