Senior AI Workbench Engineering

This is a fully remote position, open to applicants in Ireland.

📋 Description

• Design and develop AI Bench (AI Workbench) environments for experimentation and prototyping.

• Create standardized and reproducible AI development environments, including notebooks, containers, and IDEs.

• Facilitate rapid prototyping using AI frameworks like PyTorch, TensorFlow, and NVIDIA NeMo.

• Integrate AI benches with enterprise data platforms such as Cloudera, Spark, and Hadoop.

• Configure and enhance GPU-enabled environments for training and experimentation.

• Support distributed AI workloads for research and the early stages of model development.

• Provide self-service AI benches for data scientists and machine learning engineers.

• Implement standards for environment versioning, dependency management, and reproducibility.

• Monitor usage, performance, and resource utilization of the benches.

• Ensure security, access control, and isolation across all AI benches.

• Collaborate with AI Platform, Data, and MLOps teams to align bench capabilities.

⛳️ Requirements

• Over 5 years of experience in AI Workbench, ML Infrastructure, or Platform Engineering roles.

• Extensive hands-on experience with PyTorch-based experimentation environments.

• Proven experience supporting AI research and data science teams.

• Working knowledge of big data platforms, including Cloudera, Spark, and Hadoop.

• Familiarity with GPU-accelerated environments, including NVIDIA CUDA and multi-GPU setups.

• Strong experience with Docker, Kubernetes, and Linux systems.

• Proficient in Python for scripting, automation, and AI workflows.

• Familiarity with notebook and IDE tools such as Jupyter, VS Code, and remote development.

• Exposure to distributed training frameworks is a plus.

• Understanding of MLOps concepts is advantageous.

• Strong problem-solving skills and a user-centric mindset.

• Excellent communication and collaboration abilities.

• Fluent in English, both written and verbal.

🏝️ Benefits

• Clear scope with no ambiguity regarding deliverables.

• Opportunity for repeat engagements based on performance.