ML Research Engineer

Overview

Job Description

Responsibilities

• - Research, Architect, and Scale: Bring novel ideas and the content of scientific papers into high-performing and robust scientific code.
• - ML Engineering: Lead the ideation, benchmarking, and execution of complex datasets and ML models, ensuring seamless integration into our large-scale simulation frameworks.
• - Ownership of the Lifecycle: Drive software through the entire product lifecycle—from foundational research and implementation to launch and long-term support—ensuring technical excellence at every stage.

Required Skills

• - Academic Foundation: PhD, or research-focused MSc, in Computer Science, Physics, Chemistry, or a related quantitative field focused on advanced computational methods.
• - Software Excellence: Staff (5+ years) industry experience developing productionized software in professional teams.
• - Structural Biology Exposure: Experience or training in data-science related tasks related to structural biology.
• - Research Translation: Expertise translating research papers into concrete ML software artifacts.
• - Product Lifecycle Mastery: Experience supporting models in external-facing products, demonstrating the ability to bridge the gap between 'research code' and 'product code'.

Benefits

• - Competitive base salary, performance-based incentives or bonuses (where applicable), and equity participation.
• - Comprehensive medical, dental, and vision coverage for employees and dependents with generous employer premium contributions.
• - Retirement savings with company matching, paid parental leave, and inclusive family-building benefits.
• - Flexible paid time off, company-wide seasonal breaks, and support for flexible work arrangements that enable sustainable performance.
• - Opportunities for continuous learning and growth through on-the-job development, cross-functional collaboration, and access to internal learning and development programs.