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Machine Learning Technical Lead (hybrid)
Tewkesbury, United KingdomJob ID SAS20221410-91962
What makes a successful team member at L3Harris?
Check out the traits we’re looking for and see if you have the right mix.
A dynamic market environment combined with pioneering technology and a collaborative team, makes every day interesting and engaging.Thomas, Program Finance Manager, Crawley, UK
L3Harris Work Perks
- Private medical insurance and group life assurance
- Benefit allowance to help you pay for insurance
- Options for dental and critical illness coverage as well as a health cash plan and gym membership
- Employee and Family discount programme
- Employee Assistance Programme
- Optional partner life assurance
- Generous annual holiday allowance
- Retirement savings plan with employer contribution
- Employee assistance programme to provide advice and guidance on finance, mental health, and more
- Casual “dress for your day” policy
L3Harris is dedicated to recruiting and developing diverse, high-performing talent who are passionate about what they do. Our employees are unified in a shared dedication to our customers’ mission and quest for professional growth. L3Harris provides an inclusive, engaging environment designed to empower employees and promote work-life success. Fundamental to our culture is an unwavering focus on values, dedication to our communities, and commitment to excellence in everything we do.
L3Harris Technologies is an agile global aerospace and defense technology innovator, delivering end-to-end solutions that meet customers’ mission-critical needs. The company provides advanced defense and commercial technologies across space, air, land, sea and cyber domains. L3Harris has approximately $18 billion in annual revenue and 47,000 employees, with customers in more than 100 countries.
Your next role
Can you help define the future of machine learning at L3Harris?
We have a unique opportunity for an experienced specialist to lead and develop the machine learning and data science capabilities within our UK Electronic Warfare and Cyber business. This is a senior technical role with opportunities to shape, drive and influence an important new capability within the company and for our customers
You will technically lead the ML discipline as part of the enabling technology team, and guide a growing number of highly skilled data scientists and engineers. You will work on projects applying machine learning to sense, make sense and control the electromagnetic environment. You will also work to apply machine learning and data science to a broad range of technology research and development projects. As a technical authority you will support bids to bring new work into the business.
You may come from an industrial or academic background, but you will be passionate about data science and machine learning technologies and be able to lead and influence others. You may have machine learning expertise combined with an appreciation of hardware and software, and may have experience building, integrating and testing models in practical applications. You will receive dedicated and mentored on-the-job training and experience of cross-domain working to develop your skills across different areas of the business.
In return L3Harris offers exciting and rewarding projects, a very competitive salary and benefits package, and the opportunity to learn new machine learning techniques, programming languages, and a wide range of technologies, methodologies and standards.
What you’ll bring
The role of Machine Learning Technical Lead requires the following experience and skills:
- An ability to think strategically about machine learning and champion the technology within the business.
- Practical experience as a data scientist or machine learning engineer
- Experience leading others or an aptitude to lead and influence people.
- Degree qualified in Machine Learning, Engineering, Computer Science, Mathematics or similar.
- Experience with Python and numerical libraries.
- Experience with frameworks such as Tensorflow or PyTorch.
- The ability to independently perform research and exploratory tasks using publicly available software and information sources.
- Experience with the design, implementation and verification of machine learning pipelines.
- Experience interfacing machine learning or other algorithms into embedded systems.
At L3Harris, we value and appreciate everything our people do for us, and offer an attractive package. A few of our benefits are:
- Flexible working hours and hybrid working where possible
- 3.5 hour day on Fridays – finish before 12pm!
- Pension scheme of up to 7% employer contribution
- 25 days holiday per year, increasing with long service and with the opportunity to buy/sell
- Private medical insurance
- Flexible opt-in extras such as a health care cash plan, dental insurance, gym membership, critical illness cover and cycle to work scheme
- Training and development opportunities and support with qualifications where relevant
- Mental health and wellbeing schemes
Important to know
Many of our roles require the ability to obtain a security clearance relevant to the country of the position. In addition, applicants who accept a conditional offer of employment must meet eligibility requirements for access to classified information and may be subject to government security checks.
L3Harris Technologies is proud to be an Affirmative Action/Equal Opportunity Employer. We are committed to maintaining a workplace that is free from unlawful discrimination and offers equal opportunities for all. Applications from individuals are encouraged regardless of age, disability, sex, gender reassignment, sexual orientation, pregnancy and maternity, race, religion or belief, and marriage and civil partnerships.
·An ability to think strategically about machine learning and champion the technology within the business.
·Practical experience as a data scientist or machine learning engineer
·Experience leading others or an aptitude to lead and influence people.
·Degree qualified in Machine Learning, Engineering, Computer Science, Mathematics or similar.
·Experience with Python and numerical libraries.
·Experience with frameworks such as Tensorflow or PyTorch.
·The ability to independently perform research and exploratory tasks using publicly available software and information sources.
·Experience with the design, implementation and verification of machine learning pipelines.
·Experience interfacing machine learning or other algorithms into embedded systems.