Methods Worcester, England, United Kingdom
Methods Analytics is looking for a MLOps Engineer preferably has worked in the defence sector.
Location:
4-5 days/week onsite at one of the following locations: Worcester/Great Malvern/Gloucester/Poole or London
Salary:
£55,000 to £60,000 + bonus + benefits
Who we are:
Methods Analytics exists to improve society by helping people make better decisions with data. We use a collaborative, creative and user-centric approach to solve difficult problems. Ethics, privacy and quality are at the heart of our work.
What You'll Be Doing as an MLOps Engineer:
* Collaborate with Cross-Functional Teams: Work closely with data scientists, engineers, architects, and other stakeholders to align MLOps solutions with business objectives.
* Automate Workflows and Ensure Reproducibility: Write scripts to automate ML workflows and ensure reproducibility of machine learning experiments.
* Set Up ML Environments and Deployment Tools: Configure and maintain ML deployment environments using platforms and tools such as Kubernetes, Docker, and cloud platforms.
* Develop CI/CD Pipelines: Build and maintain CI/CD pipelines to streamline model deployment.
* Monitor and Maintain Deployed Models: Conduct regular performance reviews and data audits of deployed models.
* Security and Vulnerability Management: Participate in threat modelling to identify and assess potential security risks throughout the ML lifecycle.
* Troubleshoot and Resolve Issues: Proactively troubleshoot issues related to model performance and data pipelines.
* Champion Best Practices and Compliance: Ensure solutions follow best practices in security and compliance.
* Identify and Implement Reusable Solutions: Focus on reusability to maximise development efficiencies.
* Collaborate on Data Architecture: Work with data architects to ensure the MLOps pipeline integrates seamlessly within the broader data architecture.
Requirements:
* Technical Proficiency in Python and ML Frameworks: Experience with Python and ML frameworks like TensorFlow, PyTorch, or Scikit-Learn.
* Containerisation and Orchestration: Hands-on experience with containerisation and orchestration tools.
* CI/CD Expertise: Proven experience developing and managing CI/CD pipelines.
* Knowledge of Cloud and ML Infrastructure: Experience with cloud platforms and managing cloud-based ML workflows.
* Experience with Threat Modelling and Vulnerability Management: Proven ability to conduct threat modelling exercises.
* Experience in Security and Compliance: Demonstrated experience working within secure environments.
* Cross-Functional Collaboration Skills: Ability to collaborate across teams.
* Strong Troubleshooting Abilities: Proficient in diagnosing and resolving model and infrastructure-related issues.
Desirable Skills and Experience:
* Experience with MLOps Tools and Version Control: Familiarity with tools such as MLflow, DVC, and version control practices.
* Scalability and Optimisation in Production Environments: Experience managing high-performance data systems.
* Understanding of Agile Development Methodologies: Familiarity with iterative and agile development methodologies.
* Familiarity with Recent Innovations: Knowledge of recent innovations in AI and ML.
This role will require you to have or be willing to go through Security Clearance.
Benefits:
* Autonomy to develop and grow your skills and experience.
* Be part of exciting project work.
* Strong, inspiring and thought-provoking leadership.
* A supportive and collaborative environment.
As well as this, we offer:
* Development access to LinkedIn Learning.
* Wellness 24/7 Confidential employee assistance programme.
* Time off 25 days a year.
* Pension Salary Exchange Scheme with employer contribution.
* Discretionary Company Bonus based on performance.
* Life Assurance of 4 times base salary.
* Private Medical Insurance.
* Worldwide Travel Insurance.
Seniority level
Mid-Senior level
Employment type
Full-time
Job function
Information Technology
Industries
IT Services and IT Consulting
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