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)