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Senior ML Research Engineer, Virtual Cell

SandboxAQ· AI Simulation
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United Kingdom£71k - £126kFull-timePosted 3mo ago

About the role

Senior ML Research Engineer role focused on AQCell virtual cell platform. Develops and maintains ML models and data infrastructure to predict transcriptomic responses and functional endpoints from cell representations and perturbations, working with large-scale biological datasets and bridging ML with biology for drug discovery.

Responsibilities

  • Model Development: Build, train, and maintain machine learning models for expression-perturbation prediction and downstream functional-endpoint prediction (e.g. cell viability, IC50, toxicity dose-response).
  • Large-Scale Dataset Management: Acquire, harmonize, and manage large-scale biological datasets (e.g. LINCS L1000, GDSC, Tahoe-100M, DILImap) — including schema harmonization, normalization, and de-duplication across cell, drug, and assay identifiers — and manage model training pipelines over these pooled datasets.
  • Evaluation & Baselines: Contribute to automating and hardening the end-to-end evaluation pipeline, including implementing robust statistical baselines to benchmark model performance.
  • Research Translation: Translate ideas from the scientific literature into working, well-tested code integrated into the modeling framework (e.g. transformer-based perturbation models, knowledge graph and GNN-based embeddings).
  • Cross-Functional Collaboration: Partner with computational biologists, software engineers, and product stakeholders to ensure models are grounded in biology and usable in drug discovery workflows.
  • Communication: Clearly document methods, assumptions, and results, and communicate findings to technical and non-technical stakeholders.

Qualifications

  • Bachelor's degree in a scientific or quantitative field (Computer Science, Physics, Mathematics, Biology, Chemistry, or related); MS or PhD preferred.
  • Applied ML in Science: Experience building and maintaining ML models in a scientific discipline in industry; life sciences experience preferred.
  • Large-Scale Data Management: Experience managing large-scale datasets, data ingestion, cleaning, versioning, and pipeline maintenance at scale.
  • Software Engineering: Strong Python skills; experience with ML frameworks (PyTorch, JAX) and experiment tracking/data versioning tools (Weights & Biases).
  • Scientific Rigor: Ability to design sound evaluation methodology and interpret model performance against meaningful baselines.

Skills

Required:Model development for expression-perturbation predictionLarge-scale data managementPython programmingML frameworksScientific evaluation design

Benefits

  • Competitive base salary, performance-based incentives or bonuses, and equity participation.
  • Comprehensive medical, dental, and vision coverage for employees and dependents with employer premium contributions.
  • Retirement savings with company matching.
  • Paid parental leave, inclusive family-building benefits.
  • Flexible paid time off, seasonal breaks, and flexible work arrangements.
  • Opportunities for continuous learning and internal development programs.
Last updated Sep 9, 2026. Interested? Apply on the company site.

About SandboxAQ

Transforming the World with AI and Advanced Computing

SandboxAQ leverages the compound effects of AI and advanced computing to address some of the biggest challenges impacting society. SandboxAQ technologies include AI simulation, cryptography management for cybersecurity, and AI sensing for global organizations.

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