ML Research Engineer, AI for Life Sciences

SandboxAQ

ML Research Engineer driving the transition of ML prototypes into robust products at SandboxAQ. Working with a global team on AI solutions for life sciences.

Posted 7/17/2026full-timeRemote • 🇺🇸 United StatesMid-LevelSenior💰 $134,400 - $252,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in developing productionized software from research, particularly in the context of machine learning and structural biology. Proficient in MLOps practices and capable of integrating complex datasets into large-scale simulation frameworks.

Highest-signal resume keywords

PhD In Computer ScienceProductionized Software DevelopmentMachine Learning Model IntegrationMLOps PracticesBiopharma Experience

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Advanced Computational MethodsData Science TechniquesML Software Artifacts DevelopmentCommercial Software Product LaunchStructural Biology Knowledge

Tools & Technologies

Cloud PlatformsSimulation Frameworks

Industry Keywords

Interdisciplinary EnvironmentsAffinity ModelsStructure-Prediction ModelsGenerative Chemistry Models

Tech Stack

Tools & technologies

Cloud

About the role

Key responsibilities & impact

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

Requirements

What you’ll need

PhD, or research-focused MSc, in Computer Science, Physics, Chemistry, or a related quantitative field focused on advanced computational methods.
Staff (5+ years) industry experience developing productionized software in professional teams.
Experience or training in data-science related tasks related to structural biology.
Expertise translating research papers into concrete ML software artifacts.
Experience supporting models in external-facing products, demonstrating the ability to bridge the gap between "research code" and "product code".
Direct experience in biopharma or training leading-edge affinity, structure-prediction, or generative chemistry models (highly desired).
A history of developing and launching successful commercial software products within a professional engineering team (highly desired).
Familiarity with MLOps practices on major cloud platforms to support automated scaling and model monitoring (highly desired).
Experience working in interdisciplinary environments where AI intersects with physical or biological sciences (highly desired).

Benefits

Comp & perks

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.