ML Delivery Manager

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 part of our ongoing evolution to continue to be at the forefront of analysis in the open-source intelligence domain, we are now expanding our Development and Technology team to enhance the next generation of systems that will enable our customers to interconnect millions of assured data points across Janes foundational intelligence delivering the single source of truth.

Janes is searching for an Engineering Manager with a strong background in Machine Learning to join our software development team based in our Manchester office. The ideal candidate will have experience as an Engineering Manager or Delivery Lead and will have strong motivational skills and experience in coaching and guiding agile teams to achieve their full potential.

As a member of the team, you will be working closely with business analysts and product owners to shape our future deliverables in an open-source intelligence environment. You should be self-motivated and used to working in CI/CD environment, acting as a driver to improve processes and platforms.

How you will contribute to Janes

• Leading a multi-skilled delivery team of between 6 and 10 people
• Own development and operation of a portfolio of ML capabilities as part of Janes core technology platforms
• Facilitate ceremonies for the team and aid our product owners in maintaining a quality backlog.
• Help to improve the quality of features by identifying problems and suggesting improvements.
• Working with Product Owners and Business Analysts to groom and funnel the product backlog into a delivery plan.
• Coaching the team and organisation to high levels of agile maturity.
• Supporting the team using a servant leadership style,
• Facilitate discussion, decision-making, and conflict resolution.
• Building a trusting environment where problems and resolutions can be discussed without fear or judgment.
• Removing impediments and helping the team to perform at their best.
• Measure team success, using standard metrics to help drive efficiency and productivity through high levels of observability.
• Involved in the broader management of the Engineering group and its processes.
• Build and drive a clear vision and strategy for machine learning initiatives, aligned with the business goals.
• Effectively evaluate trade-offs and make data-driven decisions to achieve optimal outcomes.
• Stay up to date with the latest trends, research, and advancements in Machine Learning. You actively seek opportunities for self-improvement and encourage a culture of continuous learning and knowledge sharing within the team.

Requirements

Given the scale and complexity of what we do, we are looking for a technology leader with experience in using many of the following:

• Machine Learning
• Artificial Intelligence
• Graph Databases
• NoSQL and unstructured data
• Service Architectures
• AWS Cloud      

You'll have the following skills and experience:

• Proven working experience as an engineering manager/lead or as leader of an agile team, delivering ML or AI solutions.
• Experience with Agile project management tools such as JIRA or dev.azure
• Experience with Cloud computing services
• Experience with developing, implementing, deploying and scaling machine learning models to production,
• Experience in performing root cause analysis of production issues, performance tuning and optimization,
• Excellent communication, facilitation, negotiation, and coaching skills
• Possesses strong problem-solving and prioritization skills.
• Collaborative mentality, able to work well with peers and stakeholders

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

Last updated on Jan 23, 2024