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# Software Engineer

- **Company:** Achira Inc.
- **Location:** United States
- **Contract:** Permanent contract
- **Skills:** Amazon Web Services, Microsoft Azure, Cloud Computing, Software Debugging, Distributed Computing Environment, Distributed Systems, Job Scheduling, Performance Tuning, Tensorflow, Google Cloud, Pytorch, Autoscaling, Apache Spark, Multi-Cloud, Parallel Computation, Kubernetes, Performance Monitor, Slurm, Machine Learning Operations, Celery
- **Published:** September 4, 2026
- **Apply:** https://startup.jobs/swe-distributed-achira-8134392

## About the Role

* You are excited about and have lots of experience in building or working with distributed computing frameworks (e.g., Ray, Dask, Celery)
 * You have a good grasp of parallel computing, job scheduling, and resource management.
 * You're comfortable identifying and resolving performance issues in distributed systems (profiling, bottlenecks, network overhead)
 * You've implemented solutions using cloud compute platforms (AWS, GCP, Azure) and cluster orchestration (Kubernetes, Slurm)
 * You are familiar with popular ML frameworks (PyTorch, TensorFlow, or JAX) and MLOps best practices such as model deployment and GPU performance monitoring

## Description

* Architect & Build: Design, implement, and optimize distributed compute infrastructure for ML data processing, training, and fine-tuning.
 * Optimize & Monitor: Improve cluster observability, scheduling, and resource utilization (CPU/GPU/TPU).
 * Compute Efficiency: Research and implement cost-efficient compute solutions (spot instances, auto-scaling, multi-cloud strategies).
 * Tooling: Develop tools for monitoring, debugging, and performance tuning of large-scale ML workloads.
 * Collaboration: Collaborate with ML engineers to accelerate training pipelines and reduce bottlenecks.
 * Innovation: Stay current with emerging technologies in distributed computing (e.g., Ray, Kubernetes, Spark, Slurm) and apply them strategically.


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