Jobs at Achira

Leads People Operations for a high-growth startup, overseeing recruiting, onboarding, employee relations, performance management, compensation and benefits, compliance, HR systems, workforce planning, engagement, training, and HR reporting. Partners with leadership and legal counsel on organizational development, employment matters, immigration, and culture-building while ensuring a positive employee experience across a distributed or hybrid workforce.

As an ML Research Engineer, you'll design experiments, implement model architectures, and engineer scalable libraries to advance molecular simulations to support drug discovery.

The ML Research Engineer will develop training pipelines for atomistic simulation models and collaborate with researchers to optimize training workflows.

You will design and optimize distributed compute infrastructure for ML applications, improve resource utilization, and collaborate with ML engineers on large-scale workloads.

The role involves architecting molecular machine learning systems, building workflows for data generation and training, and collaborating between research scientists and infrastructure teams.

Conduct research to develop generative and sampling models for molecular systems, integrating probabilistic inference, deep learning, and reinforcement learning. Design, train, prototype, and benchmark diffusion, autoregressive, flow-based, and latent-variable architectures. Map between simulation and reality, collaborate with chemists and physicists, and work with engineers to deploy scalable research on distributed compute. Contribute end-to-end from ideation to production in a hybrid San Francisco/New York environment.

Develop and evaluate representation-learning architectures for atomistic systems, including equivariant GNNs and geometric transformers; design pre/mid/post-training curricula and RL strategies; prototype, benchmark, and scale research into reusable components; collaborate with physicists, chemists, and engineers to ground models in physical principles and deploy on distributed infrastructure.