DeepRec.ai
Principal Recruitment Consultant | ML & R&D Talent | Supporting Startups & Enterprises Across Europe and US
Senior AI Product Lead
$200M Backed Materials Discovery Platform USA
I’m representing a DeepTech organisation working at the intersection of advanced AI, computational chemistry, and large-scale simulation.
They are seeking an Senior Leader who can guide the platform behind their proprietary AI-driven discovery engine for molecular and electrolyte design. This system supports automated quantum simulations, real-time inference, and high-throughput evaluation for next-generation battery materials.
Your role
Define and execute the roadmap for simulation infrastructure, model training, serving, and CI CD across both AI and scientific computing
Architect systems that combine physics-based models, computational chemistry, multi-physics simulation, and machine learning
Support design and optimisation of workflows that connect molecular prediction, materials screening, and electrolyte design
Build real time inference pipelines and data frameworks that evaluate AI generated molecular or material candidates
Implement scalable data streaming, orchestration, and automated simulation systems for heavy computational workloads
Optimise GPU and CPU performance for quantum simulations, molecular modelling, and ML pipelines
Collaborate with scientists across physics, chemistry, materials science, and battery R&D to translate research into product features
Support experiment design and validation cycles by integrating lab based testing feedback into platform capabilities
Lead and mentor a small team across engineering, modelling, and ML
What we’re looking for
PhD level experience in computational science, quantum chemistry, molecular simulations, materials science, chemical engineering, applied physics, or a related field
Strong background in computational modelling such as DFT, molecular modelling, and multi physics simulation
Hands on experience in ML infrastructure, including training, serving, inference, and data pipelines
Knowledge of AI or ML applied to materials design, property prediction, or structure property modelling
Experience with high performance computing on GPU clusters or distributed systems
Domain literacy in battery chemistry, electrolyte materials, or broader materials science
Familiarity with experimental validation cycles, electrochemical testing, or lab based material evaluation is helpful
Seniority level Mid-Senior level
Employment type Full-time
Job function Research, Analyst, and Information Technology
Industries: IT Services and IT Consulting
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$200M Backed Materials Discovery Platform USA
I’m representing a DeepTech organisation working at the intersection of advanced AI, computational chemistry, and large-scale simulation.
They are seeking an Senior Leader who can guide the platform behind their proprietary AI-driven discovery engine for molecular and electrolyte design. This system supports automated quantum simulations, real-time inference, and high-throughput evaluation for next-generation battery materials.
Your role
Define and execute the roadmap for simulation infrastructure, model training, serving, and CI CD across both AI and scientific computing
Architect systems that combine physics-based models, computational chemistry, multi-physics simulation, and machine learning
Support design and optimisation of workflows that connect molecular prediction, materials screening, and electrolyte design
Build real time inference pipelines and data frameworks that evaluate AI generated molecular or material candidates
Implement scalable data streaming, orchestration, and automated simulation systems for heavy computational workloads
Optimise GPU and CPU performance for quantum simulations, molecular modelling, and ML pipelines
Collaborate with scientists across physics, chemistry, materials science, and battery R&D to translate research into product features
Support experiment design and validation cycles by integrating lab based testing feedback into platform capabilities
Lead and mentor a small team across engineering, modelling, and ML
What we’re looking for
PhD level experience in computational science, quantum chemistry, molecular simulations, materials science, chemical engineering, applied physics, or a related field
Strong background in computational modelling such as DFT, molecular modelling, and multi physics simulation
Hands on experience in ML infrastructure, including training, serving, inference, and data pipelines
Knowledge of AI or ML applied to materials design, property prediction, or structure property modelling
Experience with high performance computing on GPU clusters or distributed systems
Domain literacy in battery chemistry, electrolyte materials, or broader materials science
Familiarity with experimental validation cycles, electrochemical testing, or lab based material evaluation is helpful
Seniority level Mid-Senior level
Employment type Full-time
Job function Research, Analyst, and Information Technology
Industries: IT Services and IT Consulting
#J-18808-Ljbffr