Job reference: P2410

Senior MLOps Engineer

We are looking for Machine Learning Engineers who will thrive and show technical leadership in a fast-paced tech start-up. In this role your technical capability will be utilised in a high-energy, creative environment that will underpin a variety of product and client needs.

Role and Responsibilities

Key responsibilities for this post are:

  • Owning projects or development directives, ensuring they are delivered to defined timing and quality standards.
  • Managing and supporting more junior members on delivery-based projects.
  • Overseeing client delivery on service-based contracts, ensuring they are delivered to defined timing and quality standards.
  • Problem solving across our research and development activities.
  • Working with clients to specify user requirements, and translating these requirements into functional solutions which will be refined as part of digiLab’s core IP.
  • Contributing to new machine learning solutions, which will be refined as part of our core IP.
  • Producing quality technical output and directing/mentoring others to achieve this as part of a team.
  • Collaborating with a cross-functional team to design, develop, and maintain high-quality machine learning solutions.
  • Working with clients to specify user requirements and build tailored solutions.
  • Contributing to the architectural design, development, testing, and deployment of in-house applications.
  • Becoming a champion of, and contributing to, our probabilistic machine learning platform, ‘twinLab’.
  • Mentoring and guiding more junior engineers, fostering a collaborative and learning-oriented environment.
  • Implementing and complying with software design patterns, SOLID principles and architectural best practices.
  • Demonstrating a deep understanding of CI/CD pipelines and ensuring efficient deployment processes.
  • Collaborating with the business development team to understand and translate business requirements into technical solutions.
  • Providing technical support to customers, and leading diagnosis and mitigation in incident management investigations.

About you

Key qualifications for this role are:

  • 3-5 years of industry experience as an MLOps developer, or equivalent.
  • A masters degree in computer science, a related mathematical science, or equivalent.

Technical attributes:

  • 3-5 years of professional experience with collaborative software development.
  • Demonstrable technical leadership of projects/development activities.
  • Deep understanding of Python.
  • Deep understanding of Linux, bash, and the command line.
  • Familiarity with modern, statistical machine learning and AI techniques, including popular deployment methods.
  • Experience of building and deploying end-to-end machine learning solutions.
  • Experience with PyTorch or other deep-learning libraries.
  • Ability to write logical, consistent, self-explanatory code.
  • Collaborative use of Git/GitHub and best practices.

Team and communication attributes:

  • You will need to be adaptable, able to pivot quickly and be comfortable working in a fast-paced environment.
  • Track record of excelling as part of a team.
  • Evidence of independent or self-managed project work.
  • Excellent communication skills and examples of communicating difficult technical concepts to peers.
  • Ability to collaborate and work well as part of a fast-paced “agile” team Proven ability to lead and mentor team members.

Also desirable are:

  • Experience with security best practices and user-account management.
  • Experience of cloud deployment.
  • Strong understanding of software design patterns, SOLID and DRY principles, and architectural patterns.
  • Experience configuring and using CI/CD pipelines.
  • Knowledge of the software testing pyramid and of types of automated testing (smoke; component; unit; performance; load; end-to-end).
  • Experience with Docker and other containerisation platforms.
  • Knowledge of deployment-reliability engineering and the ability to implement reliability best practices.
  • A working knowledge of basic statistics as applied to machine learning.

We offer a range of additional benefits, including:

  • 4 day working week
  • Employee Assistance Programme (EAP) scheme
  • BUPA private health care (via salary sacrifice)

To register your interest in this position, email your C.V. and covering letter to and quote the job reference humber: P2410.