Distributed ML Systems Engineer

Achira; San Francisco (CA); On-site; USD 150,000 - 230,000; Full time

Job summary

Achira is building best-in-class foundation models for simulation in drug discovery. We seek a Software Engineer passionate about distributed computing to architect and build the infrastructure for ML data generation, model training, and fine-tuning across large-scale distributed systems.

You will ensure compute clusters are efficient, observable, cost-effective, and reliable, pushing the boundaries of ML development with emphasis on distributed systems, performance optimization, and cloud cost

Qualifications

• Experience building or operating distributed compute systems.
• Strong understanding of parallel computing and resource management.
• Experience profiling and optimizing distributed workloads.
• Hands-on with cloud platforms and cluster orchestration.
• Familiarity with ML frameworks and MLOps principles.

Responsibilities

• Architect, build, and optimize distributed compute infrastructure for ML data processing, training, and fine-tuning.
• Improve cluster observability, scheduling, and resource utilization.

Skills

Distributed computing experience

Parallel computing

Cloud platforms (AWS/GCP/Azure)

Kubernetes or Slurm

ML frameworks (PyTorch/TensorFlow/JAX)

Education

Bachelor's degree in CS or related field

Tools

Ray

Dask

Celery

Kubernetes

Spark

Slurm

Job description

Achira is building best-in-class foundation models for simulation in drug discovery. We seek a Software Engineer passionate about distributed computing to architect and build the infrastructure for ML data generation, model training, and fine-tuning across large-scale distributed systems.

You will ensure compute clusters are efficient, observable, cost-effective, and reliable, pushing the boundaries of ML development with emphasis on distributed systems, performance optimization, and cloud cost