FREE ACCESS
5,000–10,000 jobs/day
See all jobs on Scoutfield
Search thousands of fresh jobs every day.
Discover
- Fresh listings
- Fast filters
- No subscription required
Create a free account and start exploring right away.
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 capabilities in Python, cloud infrastructure, and software engineering best practices. Ability to translate complex concepts for diverse stakeholders while ensuring project feasibility and delivering impactful AI solutions.
Highest-signal resume keywords
Machine Learning Model OperationalizationPython 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
CollaborationTechnical AdvisoryStakeholder CommunicationGuiding Technical Teams
Tools & Technologies
AWSAzureGCPDockerKubernetes
Certifications & Qualifications
UK Developed Vetting (DV) Eligibility
Industry Keywords
Machine LearningAI SolutionsSoftware ArchitectureTechnical ScopingSecurity Clearance
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 ML 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
- Translate complex machine learning concepts for stakeholders
- Deliver bespoke, impactful AI solutions for diverse clients
- Contribute to scalable software architecture and define best practices
- Work with clients and cross-functional teams to ensure technical feasibility and timely delivery of high-quality, production-grade ML systems
Requirements
What you’ll need- Eligibility for UK Developed Vetting (DV) may be required
- Willingness to work on site with clients from time to time
- Experience operationalising machine learning 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 for building and managing applications at scale
- Understanding of core machine learning concepts, including probability, statistics, and common learning techniques
- Ability to guide technical teams and advise non-technical stakeholders
- Security clearance eligibility requires having lived continuously in the UK for the past 5 years
- Must be able to work in the UK; the application asks whether UK visa sponsorship is required
Benefits
Comp & perks- Opportunity to work on responsible AI with government and major technology clients
- Autonomy to own scope and deliver solutions
- Part-time hours may be discussed
- Human-reviewed applications
- Option to opt out of the AI note-taker used in interviews