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Job Overview
Location
Remote
Job Type
Full-time
Category
Software Engineering
Date Posted
December 25, 2025
Full Job Description
đź“‹ Description
- • Own the end-to-end creation of interpretable AI systems that demystify how SES’s Large Language Models and multi-agent frameworks turn terabytes of electrochemical data into next-generation battery chemistries. You will architect, train, and deploy models whose every recommendation can be traced back to physical principles, regulatory constraints, and safety margins.
- • Design and maintain massive, high-quality datasets that fuse robotic synthesis logs, in-situ X-ray diffraction streams, and first-principles simulations. You will build reproducible pipelines that version every raw file, transformation, and label so that downstream explanations remain scientifically defensible and audit-ready.
- • Invent new explainability primitives—causal graphs over molecular fragments, counterfactual generators for solvent ratios, attention heat-maps aligned with spectroscopic peaks—that let electrochemists ask, “Why did the model predict a 30 % longer cycle life?” and receive an evidence chain grounded in thermodynamics and kinetics.
- • Ship production-grade services (Python micro-services, REST/GraphQL APIs, React dashboards) that surface these explanations in real time. Your tools will integrate directly into SES’s internal experimentation platform, enabling scientists to iterate on hypotheses without leaving their lab notebooks.
- • Partner with battery modeling, robotics, and cloud teams to embed interpretability hooks at every layer: from robotic liquid-handling logs to GPU-accelerated molecular dynamics trajectories. You will ensure that every data artifact carries metadata sufficient for downstream causal analysis.
- • Establish rigorous benchmarking suites that quantify explanation faithfulness, stability, and human utility. You will open-source datasets, metrics, and baselines so the broader materials-science community can reproduce and extend SES’s advances.
- • Publish in top-tier venues (NeurIPS, ICML, Nature Energy) and present at battery conferences (ECS, IMLB) to set the global standard for trustworthy AI in energy storage. Your work will directly influence SES’s patent portfolio and regulatory filings.
- • Mentor PhD interns and junior scientists through pair programming, paper clubs, and hack-weeks. You will cultivate a culture where reproducibility, ethical AI, and fearless experimentation are non-negotiable.
- • Translate complex technical findings into board-level narratives that guide decisions on which chemistries advance to pilot-line scale, which joint ventures to pursue, and which ESG disclosures to publish.
- • Continuously scan the horizon for emerging techniques—neural ODEs, diffusion models on 3D molecular graphs, physics-informed transformers—and assess their potential to unlock even deeper scientific insight.
🎯 Requirements
- • PhD or MS in Computer Science, Machine Learning, Statistics, or related quantitative field with 3+ years post-graduate experience building interpretable or explainable AI systems.
- • Deep expertise in transformer architectures, attention mechanisms, and large-scale pre-training; hands-on proficiency with PyTorch, JAX, or TensorFlow on multi-GPU or TPU clusters.
- • Strong publication record (NeurIPS, ICML, ICLR, Nature Energy, Joule) in explainability, causal inference, or trustworthy ML applied to scientific or industrial data.
- • Production-grade software engineering: Git, Docker, CI/CD, and cloud platforms (AWS, GCP, or Azure); ability to deploy and monitor models at scale.
- • Nice-to-have: domain knowledge in chemistry, materials science, or battery technology; experience with graph neural networks, molecular representations (SMILES, SELFIES, 3D point clouds), or lab automation datasets.
🏖️ Benefits
- • Fully remote-first culture with flexible hours and asynchronous collaboration, plus quarterly on-site summits in Boston or Singapore to align with lab teams.
- • Competitive equity package (NYSE: SES) and performance bonus tied to breakthrough milestones in battery energy density and cycle life.
- • Annual $5,000 professional development stipend for conferences, courses, or certifications; dedicated 20 % “innovation time” to pursue blue-sky research.
- • Comprehensive health, dental, vision, and mental-wellness coverage for employees and dependents, plus 12 weeks of gender-neutral parental leave.
Skills & Technologies
AWS
Azure
GCP
Docker
Git
Remote
Degree Required
About SES AI Corporation
SES AI Corporation is at the forefront of accelerating the world's energy transition through advanced material discovery and battery management. The company develops high-energy and high-power density Li-Metal and Li-ion batteries, notably featuring the world's first batteries with AI-discovered electrolyte materials. These innovative solutions power a wide array of applications, including electric vehicles (EVs), Urban Air Mobility (UAMs), drones, robotics, and broader energy storage systems. With a strategic focus on global expansion, demonstrated by plans to boost cell manufacturing capacity in Korea and the acquisition of UZ Energy, SES AI is committed to revolutionizing electric transportation and beyond, ensuring safety and performance with its proprietary AI for Manufacturing and AI for Science platforms.
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