BAE Systems

Data Engineer (ML) – Gloucester – National Security

Job posted: Jun 18, 2024
Gloucester, Gloucestershire, United Kingdom
  • Salary average
    -
  • Type of employment
    Full-time
  • Remote
    No

Company

BAE Systems plc is a British multinational aerospace, defence and information security company, based in London, England. It is the largest manufacturer in Britain as of 2017. It is the largest defence contractor in Europe and the seventh-largest in the world based on applicable 2021 revenues. Its largest operations are in the United Kingdom and in the United States, where its BAE Systems Inc. subsidiary is one of the six largest suppliers to the US Department of Defense. Its next biggest markets are Saudi Arabia, then Australia; other major markets include Canada, Japan, India, Turkey, Qatar, Oman and Sweden. The company was formed on 30 November 1999 by the £7.7 billion purchase of and merger of Marconi Electronic Systems (MES), the defence electronics and naval shipbuilding subsidiary of the General Electric Company plc (GEC), with British Aerospace, an aircraft, munitions and naval systems manufacturer.

Responsibilities

  • Collaboration with cross-functional teams is essential to integrate ML models into larger systems and applications
  • Adhere to policy and ethical AI standards
  • Ensure the quality and accessibility of data used for machine learning projects is appropriate, collaborating with data engineers as necessary
  • Ensure all machine learning practices comply with policy processes and guidelines
  • Continuously explore the latest ML and AI advancements to identify methods that can enhance current systems
  • Regularly evaluate deployed models, identifying performance gaps and opportunities for optimisation
  • Handle the technical aspects of bringing models into a production environment
  • Machine Learning (ML) Engineers are responsible for designing, implementing, deploying, and maintaining artificial intelligence (AI) systems
  • Develop and deploy ML prototypes within the business, testing feasibility and impact
  • Use cloud-based environments to facilitate scalable machine learning model development and deployment across the MLOps lifecycle
  • Engineer and implement machine learning (ML) solutions
  • Guide cross-functional teams in the implementation and integration of machine learning projects
  • Perform analysis of large datasets to uncover trends, patterns, and insights that inform model development and deployment
  • Work closely with data scientists to refine, optimise, and implement models based on prototypes
  • Work as part of a wider delivery team to incorporate models into systems we design and deliver
  • Create and refine the model development and deployment strategy for better efficiency and results

Contract

40 hours per week

Candidate requirements

  • Previous experience working in the domain of Cyber Security and Intelligence is desirable, but not essential
  • Rather than specifying a list of technologies we look for, demonstrable ability in what you have used previously, along with adaptability and willingness to learn is what we value
  • A good understanding of Open Source software for Data Engineering and can evaluate these platforms against products
  • Data Engineering, Analysis or Science, with a solid understanding of programming languages along with experience of applying them in your previous role
  • Experience in using Data Engineering tools and technology ETL tools including Python and a number of the Big Data Applications
  • An understanding of maintaining and applies up to date, specialist knowledge of database concepts
  • Please note as a Data Engineer you may be required to work on client sites that are away from your base location
  • The role requires a strong foundation in software engineer, statistics, and AI/ML concepts
  • Knowledge of DevOps and MLOps is needed to ensure they can integrate with wider delivery teams
  • We are looking for experienced Data Engineers to join our team following continuous growth and success in the UK Government sector

Skills used at work

  • Accessibility
  • Artificial intelligence
  • Business
  • Design
  • Environment
  • Large datasets
  • Machine learning
  • Ml
  • Optimisation
  • Patterns
  • Performance Gap
  • Systems

Job Description

Location(s): UK, Europe & Africa : UK : Gloucester

BAE Systems Digital Intelligence is home to 4,500 digital, cyber and intelligence experts. We work collaboratively across 10 countries to collect, connect and understand complex data, so that governments, nation states, armed forces and commercial businesses can unlock digital advantage in the most demanding environments.

We are looking for experienced Data Engineers to join our team following continuous growth and success in the UK Government sector.

Our people are what differentiates us, they are resourceful, innovative and dedicated. We have a mix of generalists and specialists and recognise that this diversity contributes to our success. We recognise the benefits of forming teams from a mix of disciplines, which allows us to come up with cutting edge, high quality solutions.

Our breadth of work across the Public Sector provides diverse opportunities for our people to develop their careers in new areas of expertise and with new clients. Our projects are spread across the Data Science lifecycle from delivering Research and Proof of Concept models, to building and delivering operational solutions.

Machine Learning (ML) Engineers are responsible for designing, implementing, deploying, and maintaining artificial intelligence (AI) systems. They work closely with data scientists to understand data requirements, clean and organize data, and build efficient, scalable capabilities. The role requires a strong foundation in software engineer, statistics, and AI/ML concepts. Due to the fast-paced change in AI/ML, ML Engineers are expected to keep aware with the latest advancements in artificial intelligence and machine learning technologies, ensuring that solutions are both innovative and effective. Collaboration with cross-functional teams is essential to integrate ML models into larger systems and applications. Knowledge of DevOps and MLOps is needed to ensure they can integrate with wider delivery teams.

What you could be doing for us:

  • Engineer and implement machine learning (ML) solutions: Able to own the end-to-end process and lifecycle of ML systems.
  • Deploy models and capabilities: Handle the technical aspects of bringing models into a production environment.
  • Research new techniques: Continuously explore the latest ML and AI advancements to identify methods that can enhance current systems.
  • Collaborate with data scientists: Work closely with data scientists to refine, optimise, and implement models based on prototypes.
  • Integrate models with delivery teams: Work as part of a wider delivery team to incorporate models into systems we design and deliver.
  • Data management: Ensure the quality and accessibility of data used for machine learning projects is appropriate, collaborating with data engineers as necessary.
  • Data analysis: Perform analysis of large datasets to uncover trends, patterns, and insights that inform model development and deployment.
  • Monitor model performance: Regularly evaluate deployed models, identifying performance gaps and opportunities for optimisation.
  • Define and optimize MLOps processes: Create and refine the model development and deployment strategy for better efficiency and results
  • Adhere to policy and ethical AI standards: Ensure all machine learning practices comply with policy processes and guidelines.
  • Cross-functional technical guidance: Guide cross-functional teams in the implementation and integration of machine learning projects.
  • Innovate and prototype: Develop and deploy ML prototypes within the business, testing feasibility and impact.
  • Cloud Skills and Expertise: Use cloud-based environments to facilitate scalable machine learning model development and deployment across the MLOps lifecycle.
  • Cloud ML Services: Able to integrate pre-built cloud capabilities into a system.

What background are we looking for?

  • Data Engineering, Analysis or Science, with a solid understanding of programming languages along with experience of applying them in your previous role
  • Experience in using Data Engineering tools and technology ETL tools including Python and a number of the Big Data Applications. Rather than specifying a list of technologies we look for, demonstrable ability in what you have used previously, along with adaptability and willingness to learn is what we value
  • A good understanding of Open Source software for Data Engineering and can evaluate these platforms against products. Given a customer problem you can analyse and evaluate options and recommend solutions.
  • An understanding of maintaining and applies up to date, specialist knowledge of database concepts (including unstructured, NoSQL and ”big data” platforms), object and data modelling techniques.
  • Previous experience working in the domain of Cyber Security and Intelligence is desirable, but not essential.

How we will support you:

  • Work-life balance is important; you'll get 25 days holiday a year and, via our flexible benefits package the option to buy/sell and carry over from the year before
  • You can work around core hours with flexible and part-time working
  • Our flexible benefits package includes; private medical and dental insurance, a competitive pension scheme, cycle to work scheme, taste cards and more
  • You'll have a dedicated Career Manager to help you develop your career and guide you on your journey through BAE
  • Don't know a particular technology? Your learning and development is key to your future career
  • You'll be part of our bonus scheme

You are welcome to join any/all of our Diversity and Support groups. These groups cover everything from gender diversity to mental health and wellbeing.

Travel

Please note as a Data Engineer you may be required to work on client sites that are away from your base location. This can be for an extended period of time. In this instance, all travel and expenses costs will be covered. This will not be applicable to all Engineering projects so If you have concerns about this; please speak to your recruitment contact.

Security Clearance

Only those with the permanent and unrestricted right to live and work in the UK will be considered for a position within BAE Systems Applied Intelligence. Due to the nature of our, work successful candidates for this role will be required to go through Government SC clearance prior to starting with us. https://www.gov.uk/guidance/security-vetting-and-clearance

Life at BAE Systems Digital Intelligence

We are embracing Hybrid Working. This means you and your colleagues may be working in different locations, such as from home, another BAE Systems office or client site, some or all of the time, and work might be going on at different times of the day.

By embracing technology, we can interact, collaborate and create together, even when we're working remotely from one another. Hybrid Working allows for increased flexibility in when and where we work, helping us to balance our work and personal life more effectively, and enhance well-being.

Diversity and inclusion are integral to the success of BAE Systems Digital Intelligence. We are proud to have an organisational culture where employees with varying perspectives, skills, life experiences and backgrounds – the best and brightest minds – can work together to achieve excellence and realise individual and organisational potential.

Job posted: Jun 18, 2024

Expiration date: Jun 18, 2025