SWE - Distributed

About this role

Achira seeks a Software Engineer to design and build distributed computing infrastructure for machine learning pipelines in drug discovery. You'll optimize large-scale clusters across multiple cloud vendors, focusing on cost efficiency, reliability, and performance for ML training and data generation workflows.

What you'll do

• Architect and implement distributed compute infrastructure for ML data processing and model training
• Optimize cluster observability, scheduling, and resource utilization across CPU/GPU/TPU
• Research and deploy cost-efficient compute solutions using spot instances and multi-cloud strategies
• Develop monitoring and debugging tools for large-scale ML workloads
• Collaborate with ML engineers to reduce training bottlenecks and accelerate pipelines
• Evaluate and integrate emerging distributed computing technologies into the platform

What they're looking for

• Distributed computing frameworks (Ray, Dask, Celery)
• Parallel computing and job scheduling
• Performance profiling and bottleneck identification
• Cloud platforms (AWS, GCP, Azure)
• Cluster orchestration (Kubernetes, Slurm)
• ML frameworks (PyTorch, TensorFlow, JAX)
• MLOps and GPU performance monitoring
• System reliability and cost optimization