Machine Learning Scientist
Career Integrity & Compliance Audit Report
This vacancy has been independently reviewed by the OppaJob Transatlantic Career Intelligence Desk to confirm authentic direct employer recruiting, verify compensation transparency, and eliminate applicant processing fees.
Transatlantic Cost of Living & Purchasing Power Benchmark
Compare US ($) vs UK (£) Salary & Net Take-Home Pay
Calculate tax deductions, living costs, and purchasing power parity across US & UK metros.
Position Overview & Specifications
- Time to recharge your batteries with 270 hours of annual leave (plus every other Friday off work)
- Consideration for flexible working arrangements so that your work may fit in with your lifestyle. Just let us know on your application if you wish to work part time
- Opportunities for Professional Career Development that include funding for the annual membership of a relevant professional body, access to mentors and training
- Employee Assistance Programme and Occupational Health Services
- A generous defined contribution Group Personal Pension (we will pay between 9% and 13% of your pensionable pay depending on your own contribution)
- Life Assurance
- Discounts – access to savings on a wide range of everyday spending
- Special Leave Policy including paid time off for volunteering, public service (including reserve forces) and caring for your family
- A host of voluntary & core benefits to suit your health and wellbeing – more information available on our careers site
- Contributing solutions to real-life scientific, engineering and business challenges across AWE; producing real-life improvements to timescales, safety and quality
- Implementing, developing, testing and validating Machine Learning models for image and data processing
- Contributing to the digital future of AWE by applying Image Segmentation, Object Detection, Video/Temporal Machine Learning Techniques to large scale datasets.
- Participate in all phases of the data science lifecycle from Proof of Concept to fully tested products/solutions
- Develop deep understanding of the nuclear defence sector and the opportunities for transformation
- Degree in a STEM or IT discipline, equivalent NQF level 6 qualification or equivalent experience
- Knowledge of data collection and visualisation tools
- Knowledge of Image Segmentation, Object Detection, Video/Temporal Machine Learning Techniques
- Ability to develop code in languages like Python, with experience using packages like Tensorflow, PyTorch and OpenCV
- Ability to integrate and work well in a multi-disciplinary team
- Structured approach to problem solving
- Ability to convey complex and highly technical issues to diverse audiences
- Understanding of big data tools
- Experience of working in MS and Unix/Linux environment
- Ability to develop code (such as machine learning and AI models) in appropriate software
- Knowledge of machine learning model types and effective processes
- Understanding of parallel programming concepts
- Familiarity with software development lifecycle
Candidate Selection & Onboarding Process
Application & Resume Screening
Submit your tailored CV/Resume directly to the talent acquisition portal.
Technical & Competency Interviews
Virtual interviews with the hiring manager and multidisciplinary team.
Formal Offer & Benefits Negotiation
Written agreement outlining compensation, equity, retirement vesting, and relocation allowances.
Onboarding & Corporate Integration
Equipment provisioning, team orientation, and commencement of duties.
United Kingdom Right to Work & Skilled Worker Visa Guide
Employment in the United Kingdom requires legal Right to Work verified under the Home Office Points-Based Immigration System:
Sponsoring employers must hold an active Home Office A-rated Sponsor License and assign a valid Certificate of Sponsorship (CoS). Role must meet the general minimum salary threshold (£38,700) or occupation going rate.
Continuous employment under Skilled Worker status establishes eligibility for Indefinite Leave to Remain (ILR) after 5 continuous years, leading to British Citizenship.
Candidate Preparation Blueprint: Aerospace & Defence
Based on transatlantic hiring benchmarks for Machine Learning Scientist roles across AWE's corporate sector, successful applicants typically excel across three core dimensions:
Demonstrated portfolio evidence, architecture/system design case studies, or validated professional certifications directly applicable to Aerospace & Defence.
STAR method competency responses highlighting cross-functional leadership, conflict resolution, and delivering measurable enterprise ROI under tight timelines.
Total compensation expectation aligned within the benchmarked £31,000 - £33,000 bracket, including retirement vesting and health parity.
Explore Related Opportunities (United Kingdom)
Other high-paying verified positions matching your industry profile.
Principal Data Analytics Specialist
Senior Clinical Diagnostic Radiographer
Senior Site Reliability & Kubernetes Engineer (SRE)
Consultant Acute Care Physician (General Medicine)
Head of Cyber Security & Zero Trust Architecture
Apply for this Position
Receive high-paying Aerospace & Defence openings directly to your inbox.