Job Descriptions

Senior Machine Learning Engineer

Raytheon UK Stand: W28

Job Title: Senior Machine Learning Engineer

Location: Gloucester OR Manchester OR Remote

 

Working as part of Raytheon UK’s Cyber, Space and Training (CST) business, the Strategic Research Group (SRG) is a multi-disciplinary expert team focused on next-gen research in artificial intelligence, security research and cloud technology.

 

SRG is not yet another software team building enterprise solutions. The group operate at the cutting edge of technology and research, applying world class research to customer-relevant challenges in order to create unique prototypes, genuine expertise and valuable hands-on skills.

 

The team has grown substantially over the last 3 years providing an increasing number of opportunities for work and development in space systems, cyber security, control systems and more.

 

This is a complex and challenging role that will be highly rewarding and high profile, working in agile and successful team dedicated to deliver high quality and innovative solutions to meet complex customer requirements.

Candidate Requirements:

 

You should have hands-on experience designing, developing, deploying and managing machine learning models at scale, in production. Good verbal and written communication skills should aid your ability in working well with the team. The role involves taking novel and innovative solution through to production; so a creative, yet pragmatic mindset is welcomed.

 

The following core skills are required for the role -

 

•    Proven experience designing and implementing ML/AI pipelines.

•    Ability to write production level Python, with good software engineering fundamentals such as Test Driven Development, SOLID design patterns.

•    Experience with SQL and NoSQL databases.

 

Additional desirable skills/experience includes:

 

•    Experience with ML frameworks such as Tensorflow and PyTorch.

•    Experience in DevOps and code deployment using CI/CD best practices.

•    Good understanding of AWS or Azure platforms.

•    Exposure to Infrastructure as Code e.g. Terraform.

•    Experience with containerisation technologies.

•    Familiarity with Hadoop ecosystem and large-scale data processing frameworks e.g. Spark, Apache Beam.

•    Awareness of MLOps frameworks e.g. MLFlow, Kubeflow.

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