Ml Research Engineer Jobs in Canada {{REMOTE}}
Create alert for “ML Research Engineer”
Canada {{REMOTE}}
Top Benefits
About the role
- The AI Sim R&D team creates leading edge ML and physics-based models (“LQMs”) to advance drug and materials discovery. We are a flexible, creative, and impact driven team of multidisciplinary scientists and engineers, whose products dramatically accelerate the creation of molecules and medicines
- As a Staff ML Research Engineer, you will be the bridge between visionary research and production-grade reality, tasked with making in silico design the dominant paradigm in drug discovery. Your central purpose is to architect, scale, and optimize the scientific codebases that power our LQMs
- Over your first year, you will drive the transition of high-impact prototypes into robust products, orchestrate distributed training pipelines on world-class GPU infrastructure, and pioneer hardware-level optimizations that push the boundaries of computational chemistry
- Architect and Scale: Bring content of scientific papers into promising, scalable ML algorithms; and translate these 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
- GPU Expertise: Implement advanced software and hardware optimizations to maximize the efficiency of ML pipelines across distributed cloud GPU environments
- 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
Benefits
- Stock options
- Unlimated vacation (PTO) and flexible work culture
- Company-wide winter and summer breaks to unwind
- Best-in-class health plans: Medical, dental and orthodontics, and vision
- Family planning and fertility benefits
- Military leave
- 100% paid parental leave
- 401k with company matching
- Education stipends
- Financial wellness resources- Agentic Coding: Deep familiarity with agentic coding tools (e.g. Claude code, Codex)
- Distributed Systems: Proven experience training and optimizing large-scale ML pipelines on distributed cloud GPUs (e.g. PyTorch, TensorFlow)
- Software Excellence: Senior (5+ years) industry experience developing productionized software in professional teams
- Academic Foundation: MSc (PhD preferred) in Computer Science, Physics, Chemistry, or a related quantitative field focused on advanced computational methods
- Product Lifecycle Mastery: Experience supporting models in external-facing products, demonstrating the ability to bridge the gap between “research code” and “product code”
- Domain Expertise: Direct experience in biopharma or training leading-edge affinity, structure-prediction, or generative chemistry models
- Commercial Insight: A history of developing and launching successful commercial software products within a professional engineering team
- Advanced MLOps: Familiarity with MLOps practices on major cloud platforms to support automated scaling and model monitoring
- Collaborative Innovation: Experience working in interdisciplinary environments where AI intersects with physical or biological sciences
Not the right fit? Search for ML Research Engineer jobs in Canada {{REMOTE}}
About SandboxAQ
In the tech and data intelligence worlds, a sandbox is where innovation is born. It’s a place where the brightest free-thinking minds from across disciplines come together to reimagine what’s possible. A collaborative environment where the whole is infinitely greater than the sum of the parts.
At SandboxAQ, this forward-looking vision is core to everything we do. It’s how we became who we are and it’s how we know our solutions can shift the way your business competes in tomorrow’s marketplace. As the world enters the third quantum revolution, AI + Quantum software will address significant business and scientific challenges. SandboxAQ is a B2B company delivering AI solutions that address some of the world's greatest challenges. The company’s Large Quantitative Models (LQMs) deliver critical advances in life sciences, financial services, navigation, cyber and other sectors. The company emerged from Alphabet Inc. as an independent, growth capital-backed company in 2022, funded by leading investors including T. Rowe Price, Eric Schmidt, Breyer Capital, Guggenheim Partners, Marc Benioff, Thomas Tull, Paladin Capital Group, and others.