MLOps Engineer, Methods
£55-65k
IT services consultancy
Be an early applicant
IT services consultancy
501-1000 employees
Be an early applicant
£55-65k
501-1000 employees
Company mission
To help safeguard public-facing services and apply digital thinking to make sure the future of our public services is centred around our citizens.
Role
Who you are
- Technical Proficiency in Python and ML Frameworks: Experience with Python and ML frameworks like TensorFlow, PyTorch, or Scikit-Learn, enabling efficient deployment and management of ML models
- Containerisation and Orchestration: Hands-on experience with containerisation and orchestration tools, such as Docker and Kubernetes, to ensure reliable, scalable model deployments
- CI/CD Expertise: Proven experience developing and managing CI/CD pipelines using tools like Jenkins, Git, and Terraform, streamlining deployment and automating testing
- Knowledge of Cloud and ML Infrastructure: Experience with cloud platforms (AWS, Azure, or GCP), infrastructure-as-code (IaC) practices, and managing cloud-based ML workflows and resources at scale
- Experience with Threat Modelling and Vulnerability Management: Proven ability to conduct threat modelling exercises to identify security risks and implement vulnerability management practices to ensure robust and secure machine learning systems
- Experience in Security and Compliance: Demonstrated experience working within secure, high-assurance environments, ideally including defence or similarly regulated settings
- Cross-Functional Collaboration Skills: Ability to collaborate across teams to translate business requirements into technical specifications, maintaining clear and effective communication
- Strong Troubleshooting Abilities: Proficient in diagnosing and resolving model and infrastructure-related issues, identifying root causes, and implementing corrective actions
Desirable
- Experience with MLOps Tools and Version Control: Familiarity with tools such as MLflow, DVC, Seldon Core, Metaflow, and Airflow or Prefect, and version control practices for models and datasets to ensure reproducibility, traceability, and compliance across ML workflows
- Scalability and Optimisation in Production Environments: Experience managing high-performance, low-latency data systems and optimising ML model infrastructure to handle large-scale data in production
- Understanding of Agile Development Methodologies: Familiarity with iterative and agile development methodologies such as SCRUM, contributing to a flexible and responsive development environment
- Familiarity with Recent Innovations: Knowledge of recent innovations such as GenAI, RAG, and Microsoft Copilot, as well as certifications with leading cloud providers and in areas of data science, AI, and ML
What the job involves
- Collaborate with Cross-Functional Teams: Work closely with data scientists, engineers, architects, and other stakeholders to align MLOps solutions with business objectives, explaining complex technical concepts in accessible language for non-technical audiences
- Automate Workflows and Ensure Reproducibility: Write scripts to automate ML workflows and ensure reproducibility of machine learning experiments, enabling consistent and efficient results
- Set Up ML Environments and Deployment Tools: Configure and maintain ML deployment environments using platforms and tools such as Kubernetes, Docker, and cloud platforms (e.g., AWS, Azure), ensuring scalability and reliability
- Develop CI/CD Pipelines: Build and maintain CI/CD pipelines to streamline model deployment and ensure automated, secure, and reliable model lifecycles from development to production
- Monitor and Maintain Deployed Models: Conduct regular performance reviews and data audits of deployed models, tracking model drift and identifying opportunities for optimisation to enhance performance and reliability
- Security and Vulnerability Management: Participate in threat modelling to identify and assess potential security risks throughout the ML lifecycle. Implement and maintain vulnerability management practices to proactively address security risks, ensuring the integrity and resilience of deployed models and infrastructure
- Troubleshoot and Resolve Issues: Proactively troubleshoot issues related to model performance, data pipelines, and infrastructure, identifying and resolving root causes to maintain stability
- Champion Best Practices and Compliance: Ensure solutions follow best practices in security, scalability, and compliance, particularly aligning with Secure by Design and high-assurance software requirements
- Identify and Implement Reusable Solutions: Focus on reusability to maximise development efficiencies, reducing costs across programmes by identifying commonalities and building scalable solutions
- Collaborate on Data Architecture: Work with data architects to ensure the MLOps pipeline integrates seamlessly within the broader data architecture, aligning with governance and compliance standards
Application process
- This role will require you to have or be willing to go through Security Clearance. As part of the onboarding process candidates will be asked to complete a Baseline Personnel Security Standard; details of the evidence required to apply may be found on the government website
- If you are unable to meet this and any associated criteria, then your employment may be delayed, or rejected. Details of this will be discussed with you at interview
Our take
The UK public sector has long understood the need for digital transformation, but antiquated systems and outdated processes can make even the most ambitious plans for adaptation fall short. Methods has existed for more than 30 years to assist government departments and agencies make the leap, helping them understand the possibilities of digital transformation and guiding them through strategic planning, data migration and implementation phases.
Methods is an acknowledged leader in IT consultancy within the public sector, praised for their human touch and focus on sustainability which it believes sets it apart from firms. Indeed it is trusted by huge swathes of the UK public sector including the NHS, the Office for National Statistics, the Cabinet Office and the Ministry of Defence, to name just a few.
Methods was acquired by the Alten Group in mid-2022. This acquisition will help to reinforce Method's position as a leading player in the public sector while also allowing it to broaden its role in the private sector. It is poised for growth and is investing heavily in talent to make this a reality.
Steph
Company Specialist at Welcome to the Jungle
Insights
Few candidates hear
back within 2 weeks
Company
Company benefits
- Autonomy to develop and grow your skills and experience
- Be part of exciting project work that is making a difference in society
- Strong, inspiring and thought-provoking leadership
- A supportive and collaborative environment
- Development access to LinkedIn Learning, a management development programme and training
- Wellness 24/7 Confidential employee assistance programme
- Social - Breakfast Tuesdays, Pizza Thursday monthly, weekly social in the office and commitment to charitable causes
- Time off 25 days a year
- Pension Salary Exchange Scheme with 4% employer contribution and 5% employee contribution
- Discretionary Company Bonus based on company and individual performance
- Life Assurance of 4 times base salary
- Private Medical Insurance which is non-contributory (spouse and dependants included)
- Worldwide Travel Insurance which is non-contributory (spouse and dependants included)
- Benefits Platform offering various retail and leisure discounts
Company HQ
Farringdon, London, UK
Articles
Leadership
Pat Crossley-Smith
(Executive Diretor (Not Founder))Previously worked in Agile Product at BUPA and Senior Manager in Development at British Airways.
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