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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in developing and delivering machine learning solutions, with a strong focus on AI/ML algorithms, technical leadership, and effective communication with stakeholders. Proven ability to mentor team members and contribute to research initiatives in data science.
Highest-signal resume keywords
Machine Learning Solutions DeliveryPython ProgrammingAI/ML Algorithms ExpertiseTechnical LeadershipMentoring Team Members
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 LearningData SciencePythonHuggingFaceTensorFlowPyTorchGenerative AINatural Language ProcessingComputer VisionAI Model Training
Soft Skills
Effective CommunicationCollaborationMentoring
Tools & Technologies
ML PipelinesDockerAWSGCPAzureLinux Systems
Certifications & Qualifications
SC ClearanceEDV Clearance
Industry Keywords
Research PublicationsTechnical Project ProposalsAcademic Research
Tech Stack
Tools & technologiesAWSAzureCloudDockerGoogle Cloud PlatformLinuxPythonPyTorchTensorflow
About the role
Key responsibilities & impact- Develop complex, novel data science solutions with minimal guidance
- Contribute significantly to machine learning projects
- Scope, design and deliver data-centric solutions collaboratively across disciplines
- Undertake research and applied AI/ML tasks on customer and internal research projects
- Generate ideas for new research directions
- Provide technical leadership in small project groups
- Mentor junior team members within project teams and the wider Strategic Research Group
- Work with customers and internal stakeholders to determine appropriate technical approaches
- Perform technical development required for project delivery
- Support AI/ML projects from initial idea scoping through final delivery in customer and internal domains
- Communicate ideas effectively to senior technical leaders to inform project technical direction
Requirements
What you’ll need- BSc in Machine Learning, Data Science, Computer Science, Mathematics or related field
- Experience coding in Python and associated ML packages (HuggingFace, TensorFlow, PyTorch)
- Established track record of delivering ML solutions to customers and internal stakeholders
- Deep understanding of AI/ML algorithms for different data types and tasks, including Generative AI, NLP and computer vision
- Experience training and developing AI models including Large Language Models
- Ability to produce high-quality scientific writing for internal and external stakeholders and academic publications
- Experience mentoring team members and providing technical leadership on small projects or sub-parts of larger deliveries
- Must already hold or be able to gain SC clearance and eDV clearance once started
- PhD or Master's degree highlighting experience of academic research (desirable)
- Experience using robust ML pipelines, version control and environment management such as venvs or Docker (desirable)
- Working knowledge of Linux systems and basic command-line functionality, including AWS CLI and Docker CLI (desirable)
- Experience deploying AI models scalably for external users (desirable)
- Experience working in Cloud, preferably AWS, GCP or Azure (desirable)
- Research publications in peer-reviewed journals (desirable)
- Experience writing technical project proposals (desirable)
Benefits
Comp & perks- 37hr working week with early finish Fridays
- 25 days holiday + statutory public holidays
- Opportunity to buy and sell up to 5 days
- Up to 5 paid days volunteering
- Contributory Pension Scheme (up to 10.5% company contribution)
- Annual company bonus scheme (discretionary)
- 6 times salary Life Assurance with pension
- Flexible Benefits scheme with salary sacrifice schemes, including Health Cashplan, Dental, and Cycle to Work
- Enhanced sick pay
- Enhanced maternity, paternity & shared parental leave
- Flexible working culture
- Opportunities for professional development
- Collaborative environment