Machine Learning DevOps

📋 Job Overview

Pathway is searching for a Machine Learning DevOps with experience in cloud and compute cluster management, scaling infrastructures, and Linux administration. Our development, ML training, and production environment is in the cloud, using several major cloud providers. We need support in managing and automating the processes, and scaling the infrastructure to growing team and production needs.

🏢 About Pathway

Pathway is shaking the foundations of artificial intelligence by introducing the world’s first post-transformer model that adapts and thinks just like humans. Pathway’s breakthrough architecture (BDH) outperforms Transformer and provides the enterprise with full visibility into how the model works. Combining the foundational model with the fastest data processing engine on the market, Pathway enables enterprises to move beyond incremental optimization and toward truly contextualized, experience-driven intelligence. The company is trusted by organizations such as NATO, La Poste, and Formula 1 racing teams.

🎯 The Role

We are currently searching for a Machine Learning DevOps with experience in cloud and compute cluster management, scaling infrastructures, and Linux administration. Our development, ML training, and production environment is in the cloud, using several major cloud providers. We need support in managing and automating the processes, and scaling the infrastructure to growing team and production needs.

✅ Key Responsibilities

• Optimize infrastructure for ML training and inference (e.g., GPUs, distributed compute).
• Automate and maintain ML/LLM pipelines (data ingestion, training, validation, deployment).
• Manage model versioning, reproducibility, and traceability.
• Work with terabyte-large datasets.
• Implement ML-centric CI/CD practices.
• Monitor model performance and data drift in production.
• Collaborate with machine learning engineers, software engineers, and platform teams.

📌 Required Qualifications

• Very good familiarity with Linux, shell scripts, and cluster configuration scripts as the basic work tool.
• Proficiency in workload management, containerization and orchestration (Slurm, Docker, Kubernetes).
• Solid grasp of CI/CD tools and workflows (GitHub Actions, Jenkins, Gitlab CI, etc.).
• Cloud infrastructure knowledge (AWS, GCP, Azure) – especially in ML services (e.g., SageMaker Hyperpod, Vertex AI).
• Familiarity with monitoring/logging tools (Grafana, CloudWatch, Prometheus, Loki).
• Experience with infrastructure as code (Terraform, CloudFormation, cluster-toolkit).
• Experience with ML pipeline orchestration tools (e.g., MLflow, Kubeflow, Airflow, Metaflow).
• Programming skills in Python (with exposure to ML libraries like TensorFlow, PyTorch).
• Experience with cluster, systems, and networks administration.
• Willingness to learn.

⭐ Desirable Experience

• Base salary: Competitive based on profile and location.
• Minimum requirement of a BSc in Computer Science or Information Technology.
• Experience with ambitious efforts such as contributions to the Linux kernel, bug bounties, academic grid/cluster computing, or sports championships.

🎁 Benefits

• Type of contract: Permanent employment contract
• Preferable joining date: Immediate.
• Compensation: based on profile and location.
• Location: Remote work. Possibility to work or meet with other team members in one of our offices: Palo Alto, CA; Paris, France or Wroclaw, Poland. Candidates based anywhere in the EU, United States, and Canada will be considered.

🛂 Visa & Eligibility

• Candidates based anywhere in the EU, United States, and Canada will be considered.