Senior Artificial Intelligence Engineer

3 days ago


Manchester, United Kingdom Janes Full time

At Janes, we empower militaries, governments, and defence companies to make informed decisions with our cutting-edge open-source intelligence solutions.

We combine expert-driven tradecraft developed over 120 years with human-machine teaming to deliver assured data across military capabilities, equipment, events, countries, companies, and markets.

Our data model creates a framework of interconnected defence intelligence by linking millions of assured data points, enabling our customers to integrate all relevant data into a single environment for more complete and accurate answers.

As a Senior Machine Learning Engineer at Janes, you will play a crucial role in developing and implementing sophisticated artificial intelligence products. Your responsibilities will involve designing and constructing machine learning models, refining existing systems, and collaborating with cross-functional teams.

To thrive in this position, you must possess exceptional skills in statistics, programming, data science, and software engineering principles, as well as a strong understanding of machine learning concepts and algorithms.

Your goal will be to create highly efficient self-learning applications that can adapt and evolve over time, pushing the boundaries of AI technology. In return, we offer a competitive salary range of $140,000 - $180,000 per annum, depending on experience, along with a comprehensive benefits package, including 27 days of annual leave, healthy half-day leave every 6 months, pension plan, private medical insurance, life cover, and access to GoodHabitz.

Key Responsibilities:

  • Study and transform data science prototypes
  • Design machine learning systems
  • Research and implement appropriate ML algorithms and tools
  • Develop machine learning applications according to requirements
  • Select appropriate datasets and data representation methods
  • Run machine learning tests and experiments
  • Perform statistical analysis and fine-tuning using test results
  • Train and retrain systems when necessary
  • Extend existing ML libraries and frameworks
  • Keep abreast of developments in the field


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