ML Engineer (AI)

Location: Remote. The primary lab and office is in South San Francisco; the organization also holds quarterly co-working weeks there and an annual offsite.

Company

hirify.global is a frontier therapeutics company using AI, multimodal oncology data, and foundation models to support precision drug discovery and clinical outcome prediction.

What you will do

• Design and evolve systems for distributed model training and batch inference.
• Build experiment-tracking, model-evaluation, and model-registry workflows that support reproducibility.
• Profile and optimize PyTorch training and inference across GPU utilization, memory, data loading, communication, and checkpointing.
• Develop researcher-facing CLIs, SDKs, and job-submission tools for large-scale runs.
• Operate reliable, observable, and cost-efficient GPU infrastructure using Kubernetes, AWS, Ray, Kueue, Docker, Terraform, and high-performance networking.
• Work with ML researchers to troubleshoot issues and translate research needs into platform improvements.

Requirements

• Strong software engineering fundamentals and experience operating production ML systems.
• Hands-on experience with distributed model training and multi-GPU workloads.
• Experience with PyTorch or a similar deep-learning framework, including profiling, debugging, and modifying training and inference code.
• Experience resolving performance bottlenecks across ML workloads, data pipelines, GPUs, memory, distributed communication, and infrastructure.
• Experience with cloud and compute infrastructure, containers, Kubernetes, GPU systems, storage, networking, and distributed compute.
• Strong collaboration skills and several years of experience in production ML systems, distributed training, or ML infrastructure.

Nice to have

• Experience with Ray, Kubernetes, Kueue, MLflow, Terraform, NCCL, or EFA.
• Experience optimizing large-scale training, batch inference, or online model serving.
• Experience operating GPU clusters in AWS or another major cloud environment.
• Experience with FSDP, DeepSpeed, profiling tools, CUDA-level debugging, or low-level GPU optimization.

Culture & Benefits

• Collaborative, interdisciplinary environment focused on solving difficult scientific and technical problems.
• Remote work supported through Slack, Zoom, and distributed collaboration practices.
• Health, dental, and vision insurance with premiums fully covered for employees and dependents depending on plan choice.
• Flexible PTO, nine paid holidays, synchronized company breaks, and parental leave.
• Stock options, a 401(k) plan with employer match, disability, life, and AD&D insurance.
• HSA, FSA, dependent-care savings, mental-health resources, and additional financial and lifestyle programs.