Janes enables militaries, governments, and defence companies to make critical decisions. Our expert-driven tradecraft, developed over 120 years, combined with human-machine teaming, delivers assured open-source intelligence across military capabilities and order of battle, equipment, events, countries, companies, and markets.
Linking millions of assured data points, Janes data model creates a framework of interconnected open source defence intelligence. This allows our customers to integrate all relevant data and connections into a single intelligence environment to deliver a more complete and accurate answer. Using Janes, our customers can use their scarce resource more effectively, to get to better decisions with higher confidence, more quickly.
Job purpose
As a Senior Machine Learning Engineer, you will play a crucial role in the development and implementation of cutting-edge artificial intelligence products. Your responsibilities will involve designing and constructing sophisticated machine learning models, as well as refining and updating existing systems.
In order to thrive in this position, you must possess exceptional skills in statistics and programming, as well as a deep understanding of data science and software engineering principles.
Your ultimate objective will be to create highly efficient self-learning applications that can adapt and evolve over time, pushing the boundaries of AI technology. Join us and be at the forefront of innovation in the field of machine learning.
How you will contribute at Janes
- 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
Requirements
- Proven track record as a highly commercially experienced ML Engineer having owned the design, implementation and deployment of end to end solutions
- Ability to write robust code in Python and preferably also in JavaScript
- Strong understanding of Natural Language Processing (NLP)
- Familiarity with machine learning frameworks (Pytorch, HuggingFace) and libraries (like scikit-learn)
- Experience in AWS or other similar cloud platforms
- Excellent communication skills
- Ability to work in a team
Desirable skills
- Understanding of data structures, data modelling and software architecture
- Deep knowledge of math, probability, statistics and algorithms
- Understanding and ability to orchestrate resources in cloud (Terraform)
- Defining data augmentation pipelines
- Analysing the errors of the model and designing strategies to overcome them
- Deploying models to production
- Outstanding analytical and problem-solving skills
Benefits
- 27 days of annual leave
- Healthy half (0.5 day leave every 6 months for wellbeing)
- Leave (study / volunteer / reserve forces)
- Pension plan (6% employer contribution)
- Private medical insurance – Vitality
- Maternity (100% of basic salary for the first 26 weeks followed by Statutory Maternity Pay)
- Paternity (100% of basic salary for 6 weeks)
- Life cover
- Access to GoodHabitz
