Senior ML Research Engineer, Virtual Cell
SandboxAQ · Remote · Canada ·
COMPENSATION
€•• – ••k
Listed on the employer's job board (Ashby)
- Senior level role
- Fully remote
- Python + PyTorch/JAX
- Drug discovery focus
- Equity participation
Join the AI Sim R&D team at SandboxAQ to advance drug discovery through Large Quantitative Models. You will work on AQCell, a virtual cell platform that predicts biological repercussions of compounds by mapping transcriptomic responses to functional endpoints like cell viability and toxicity.
As a Machine Learning Engineer, you will build and maintain the data infrastructure and models powering this pipeline. The role sits at the intersection of machine learning and biology, requiring collaboration with computational biologists and software engineers to scale models for real-world decisions.
What you'll do
- Build and train ML models for expression-perturbation and functional-endpoint prediction
- Acquire, harmonize, and manage large-scale biological datasets like LINCS L1000
- Automate and harden end-to-end evaluation pipelines with robust statistical baselines
- Translate scientific literature ideas into tested code within the modeling framework
- Partner with biologists and engineers to ensure models are biologically sound
- Document methods and communicate findings to technical and non-technical stakeholders
What you'll need
- Bachelor's in CS, Physics, Math, Biology, or related field; advanced degree preferred
- Experience building and maintaining ML models in an industry science setting
- Proven ability to manage large-scale datasets and model training pipelines
- Strong Python skills with experience in PyTorch, JAX, and tools like Weights & Biases
- Ability to design sound evaluation methodologies and interpret model performance
Nice to have
- Experience with transcriptomics harmonization and normalization tools
- Familiarity with public perturbation datasets like GDSC or DepMap
- Knowledge of graph neural networks or knowledge graph embeddings
- Familiarity with cheminformatics representations like SMILES or InChI keys
- Background in interdisciplinary environments combining AI and biology
Stack
- Python
- PyTorch
- JAX
- Weights & Biases
- LINCS L1000
- GDSC
- Tahoe-100M
- DILImap
How you'll work
- Fully remote work arrangement
- Flexible work arrangements supported
- Global team environment
What you get
- Competitive base salary and equity participation
- Performance-based incentives or bonuses
- Comprehensive medical, dental, and vision coverage
- Retirement savings with company matching
- Paid parental leave and family-building benefits
- Flexible paid time off and seasonal breaks
- Access to internal learning and development programs