Machine Learning Engineer

Faculty transforms organizational performance through safe, impactful and human-centric AI, serving over 300 global customers.
Machine Learning
Mid-Level Software Engineer
Hybrid
3+ years of experience
AI · Enterprise SaaS · Defense

Description For Machine Learning Engineer

Faculty is a pioneering AI company that transforms organizational performance through safe, impactful, and human-centric AI solutions. As a Machine Learning Engineer, you'll join a dynamic team working on cutting-edge ML applications in the Defense sector. The role combines engineering excellence with ML expertise, focusing on building production-grade systems and infrastructure.

You'll work in Faculty's Old Street office and client locations in a hybrid setup, spending up to three days per week client-side. The position offers unique opportunities to work on high-impact problems in the National Security space, requiring security clearance eligibility.

The ideal candidate combines technical expertise with a scientific mindset and pragmatic approach. You'll be responsible for the entire ML lifecycle, from working with data scientists to deploy models, to creating scalable tools and infrastructure. Experience with cloud platforms, containers, and ML frameworks is essential.

Faculty offers a distinctive professional environment where you'll work alongside brilliant minds from diverse backgrounds. The company serves over 300 global customers, providing software, AI consultancy, and runs an award-winning Fellowship programme. This role presents an exceptional opportunity to shape the future of AI applications while working with leaders from government, academia, and global tech.

The position offers significant growth potential in a rapidly evolving organization, where you'll contribute to solving real-world problems using cutting-edge technology. You'll be part of a team that values innovation, pragmatic solutions, and responsible AI development, making a meaningful impact in the defense and security sector.

Last updated a minute ago

Responsibilities For Machine Learning Engineer

  • Design, build, and deploy production-grade software, infrastructure, and MLOps systems
  • Build software and infrastructure that leverages Machine Learning
  • Create reusable, scalable tools to enable better delivery of ML systems
  • Work with customers to understand their needs
  • Work with data scientists and engineers to develop best practices
  • Implement and develop Faculty's view on ML software operationalization
  • Work in cross-functional teams to deliver sophisticated systems
  • Scope projects and design systems with senior engineers
  • Provide technical expertise to customers

Requirements For Machine Learning Engineer

Python
Kubernetes
  • Understanding of and experience with the full machine learning lifecycle
  • Experience working with Data Scientists to deploy trained ML models into production
  • Experience with common ML frameworks (Scikit-learn, TensorFlow, or PyTorch)
  • Software engineering best practices and Python development
  • Experience with cloud architecture, security, deployment (AWS, GCP or Azure)
  • Experience with Docker and Kubernetes
  • Understanding of probability and statistics
  • Experience managing/mentoring junior team members
  • Outstanding verbal and written communication
  • Must be eligible for Security Clearance

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