ML Engineer - Infrastructure

Convergence; London; On-site; GBP 60,000 - 100,000; Full time

Job summary

A leading company in AI technology is seeking a Machine Learning Engineer to design and implement cutting-edge ML infrastructures. The role involves collaboration with data scientists and ML engineers to create robust solutions enhancing productivity and creativity. This position offers opportunities for growth and involvement in impactful projects as part of a dynamic team focused on transforming AI integration in daily life.

Benefits

Professional growth opportunities

Collaborative work environment

Competitive salary and benefits

Qualifications

• 3+ years of experience in ML infrastructure or platform engineering.
• Strong proficiency in Python for ML pipeline automation.
• Extensive experience with Slurm cluster management.

Responsibilities

• Design and maintain ML-focused cloud infrastructure on GCP.
• Build and manage HPC clusters for distributed ML workloads.
• Implement monitoring solutions for ML model performance.

Skills

Machine Learning Infrastructure

Python

HPC Clusters Management

Monitoring and Logging

Problem Solving

Tools

Terraform

Slurm

GCP

Job description

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At Convergence, we're transforming the way AI integrates into our daily lives. Our team is developing the next generation of AI agents that don't just process information but take actions, learn from experience, and collaborate with humans. By introducing Large Meta Learning Models (LMLMs) that integrate memory as a core component, we're enabling AI to improve continuously through user feedback and acquire new skills during real-time use.

We believe in freeing individuals and businesses from mundane, repetitive tasks, allowing them to focus on innovative and creative work that truly matters. Our personalised AI assistant, proxy, collaborates with users to enhance productivity and creativity. With a $12 million pre-seed funding from Balderton Capital, Salesforce Ventures, and Shopify Ventures, we're poised to make a significant impact in the AI space. Join us in shaping the future of human-AI collaboration and be part of our mission to transform the AI landscape.

Responsibilities

• Design, implement, and maintain our ML-focused cloud infrastructure on GCP using Infrastructure as Code (Terraform)
• Build and manage HPC clusters with Slurm for distributed ML workloads, focusing on GPU/TPU utilization and job scheduling
• Develop and maintain ML pipeline automation tools and ML-specific CI/CD workflows in Python
• Design and optimize data storage solutions for ML datasets, model artifacts, and feature stores
• Implement comprehensive monitoring, logging, and alerting solutions for ML model performance and infrastructure health
• Collaborate with ML engineers and data scientists to provide robust infrastructure for model training and deployment
• Lead and implement security best practices for ML systems, including model security and data protection

Requirements

• 3+ years of experience in ML infrastructure or ML platform engineering
• Strong proficiency in Python for ML pipeline automation and tooling
• Extensive experience with Slurm cluster management for large-scale ML workloads
• Proven track record with Terraform and Infrastructure as Code for ML environments
• Solid understanding of GCP's ML-specific services (Vertex AI, AI Platform, etc.)
• Experience with distributed training systems and model serving infrastructure
• Experience with ML observability tools and performance monitoring
• Excellent problem-solving skills with a focus on ML system reliability and optimization

Bonus Qualifications

• Knowledge of ML-specific orchestration tools (e.g., MLflow, Ray)
• Experience with high-performance computing for ML training
• Contributions to ML infrastructure-related open-source projects
• Experience with GPU/TPU cluster management and optimization
• Background in ML operations (MLOps) or AI reliability engineering
• Familiarity with vector databases and efficient embedding storage/retrieval

Why Join Us?

• Be at the cutting edge of AI and LLM technology
• Work on challenging problems that impact users' daily lives
• Collaborative and innovative work environment
• Opportunities for professional growth and learning
• Competitive salary and benefits package

Seniority level

• Seniority level

  Mid-Senior level

Employment type

• Employment type

  Full-time

Job function

• Job function

  Information Technology

• Industries

  Research Services

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