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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in building and deploying production-grade machine learning systems, with strong proficiency in Python and experience across the full machine learning lifecycle. Capable of collaborating with cross-functional teams and advising stakeholders on complex technical concepts.
Highest-signal resume keywords
Machine Learning Lifecycle ExperiencePython ProgrammingCloud Platforms (AWS, Azure, GCP)Docker and KubernetesSoftware Engineering Best Practices
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Machine LearningPythonScikit-learnTensorFlowPyTorchCloud InfrastructureDockerKubernetesProbabilityStatistics
Soft Skills
Excellent CommunicationAdvising Non-Technical Stakeholders
Certifications & Qualifications
UK Developed Vetting (DV) Eligibility
Industry Keywords
Production-Grade ML SystemsScalable SolutionsTechnical ScopingArchitectural DecisionsBest Practices
Tech Stack
Tools & technologiesAWSAzureCloudDockerGoogle Cloud PlatformKubernetesPythonPyTorchScikit-LearnTensorflow
About the role
Key responsibilities & impact- Build and deploy production-grade machine learning software, tools, and infrastructure
- Create reusable, scalable solutions that accelerate delivery of machine learning systems
- Collaborate with engineers, data scientists, and commercial leads to solve critical client challenges
- Lead technical scoping and architectural decisions to ensure project feasibility and impact
- Define and implement Faculty’s standards for deploying machine learning at scale
- Act as a technical advisor to customers and partners, translating complex machine learning concepts for stakeholders
- Contribute to scalable software architecture and define best practices
- Ensure technical feasibility and timely delivery of high-quality, production-grade ML systems
Requirements
What you’ll need- Experience across the full machine learning lifecycle and operationalising models built with Scikit-learn, TensorFlow, or PyTorch
- Strong Python skills
- Solid experience with software engineering best practices
- Hands-on experience with cloud platforms and infrastructure such as AWS, Azure, or GCP, including architecture and security
- Experience with Docker and Kubernetes
- Understanding of probability, statistics, and common machine learning techniques
- Excellent communication skills and ability to advise non-technical stakeholders
- May need to be eligible for UK Developed Vetting (DV)
- Must have lived in the UK continuously for the past 5 years for security clearance eligibility
- Must be willing to work on site with clients from time to time
- May be required to travel throughout the UK on a weekly basis for Defence team work
- Visa sponsorship requirement for work in the UK must be disclosed
Benefits
Comp & perks- Hybrid working arrangement
- Part-time hours may be possible
- Opportunity to work on impactful, production-grade AI solutions
- Interview AI note-taker opt-out available