Generative AI Researcher - Atomistic Foundation Models

Invent the next generation of deep generative, representational, and simulation models for molecules and materials - building the foundation models that make the atomistic world learnable, predictable, and designable.

Why Achira

• Join a world-class, interdisciplinary team of ML researchers, physicists, chemists, and engineers reimagining atomistic simulation through large-scale foundation models.
• Push the frontier where deep learning meets the laws of nature - bridging generative AI, probabilistic reasoning, and molecular physics.
• Work at a scale few attempt: massive data, massive compute, and massive ambition.
• Own your research end-to-end - from concept and architecture to training, evaluation, and deployment.
• Thrive in a culture that rewards rigor, velocity, creativity, and impact - not bureaucracy.

About the Role

Achira is building foundation simulation models - large-scale models that learn the structure, dynamics, and energetics of the atomistic world.

These models unify deep representation learning, generative modeling, and advanced simulation and sampling.

As a Generative AI Researcher, you will:

• Design and train frontier deep generative models - diffusion, autoregressive, flow-based, and latent-variable architectures - for molecules, materials, and atomic systems.
• Develop expressive representations of molecular and atomistic structure and dynamics, including equivariant graph neural networks, geometric transformers, and latent encoders that capture physical symmetries and constraints.
• Invent advanced sampling and simulation methods that integrate probabilistic inference, deep learning, and reinforcement learning - enabling efficient exploration and simulation of learned energy landscapes.
• Build models that understand, generate, and simulate the physical world - unifying reasoning, simulation, and prediction.
• Collaborate with physicists and chemists to ground models in ab initio, molecular dynamics, and experimental data.
• Prototype, benchmark, and iterate rapidly - transforming research ideas into reusable, scalable model components across Achira's foundation model stack.
• Contribute to publications, open-source tools, and internal research projects that advance the field.

About You

You are a deep learning researcher who moves seamlessly between representation learning, generation, and simulation - motivated by the idea of teaching AI to reason about the physical world.

Required Qualifications

• PhD or equivalent research experience in machine learning, physics, chemistry, computer science, or a related field.
• Proven expertise in deep generative modeling (e.g., diffusion, VAEs, flows, autoregressive transformers).
• Experience in representation learning for structured data, especially graph or 3D geometric models (GNNs, SE(3)/E(3)-equivariant networks, geometric transformers).
• Proficiency in Python and modern ML frameworks (PyTorch, JAX, Tensor Flow) plus scientific libraries (Num Py, Sci Py, ASE, MD Analysis).
• Solid grounding in probability, optimization, and deep learning fundamentals.
• Demonstrated research impact through publications, open-source contributions, or released models.

Preferred Qualifications

• Experience with atomistic simulations, molecular dynamics, or electronic-structure data.
• Familiarity with probabilistic inference, MCMC, variational methods, or reinforcement learning for sampling and control.
• Experience integrating physics-informed priors or energy-based models into deep architectures.
• Knowledge of atomistic molecular datasets and benchmarks such as QM9, MD17, OC20/22, and SPICE.
• Experience scaling models on HPC or distributed GPU infrastructure.
• Strong technical communication across interdisciplinary teams.

What Success Looks Like

• You develop models that both represent and generate molecular systems, and simulate their dynamics through learned sampling and reasoning.
• Your architectures and algorithms become core components of Achira's foundation model platform.
• You thrive in collaborative interdisciplinary environments.
• You help define the next era of generative and simulation AI for the physical sciences.

Join Us

At Achira, we're teaching machines to understand and simulate the laws of nature - making matter itself generative, interpretable, and designable.

If you think deeply, build boldly, and dream in equations, tensors, and compute graphs, we want you on our team.