Senior Machine Learning Engineer, Multiverse

• You will need to be analytical, creative and collaborative, with a strong understanding of algorithm development and the ability to work within a fast paced team environment
• Take a tenacious, curious, and pragmatic approach to problem solving, with a focus on generating usable and scalable outputs
• Possess a meticulous attention to detail
• Have a growth mindset and a desire to continuously develop
• Feel connected and committed to Multiverse’s mission and values
• Deep expertise in software engineering and machine learning engineering, gained from prior experience working on a production engineering team
• Strong backend engineering ability and understanding of engineering best practices (CI/CD, version control, cloud environments, observability, configuration management)
• In-depth experience with Python and strong command of databases (e.g. PostgreSQL), data structures, and algorithms
• In-depth knowledge of one or more of the major machine learning frameworks (e.g., PyTorch or TensorFlow)
• Ability to manage machine learning projects and clearly communicate outcomes to technical and non-technical audiences

Desirable

• As a Machine Learning Engineer at Multiverse, you will design, build and deploy models and algorithms that will power our external customer-facing product experiences
• You will leverage our unique data-sets to develop truly differentiated data science, machine learning & artificial intelligence- based assets, helping transform Multiverse into a true AI-first company
• This role will be within the AI Team, working closely with other ML Engineers, Data Scientists, ML Ops Engineers, Product Managers
• The AI Team’s mission is to build the intelligence layer at Multiverse that fuels captivating educational experiences, drives effective and continuous digital transformation for enterprises, and empowers Multiverse coaches and operations with tools that scale our teaching capabilities
• You will also collaborate closely with key stakeholders from our Product, Engineering & other teams across the business - often working in cross-functional squads alongside experts from across other disciplines
• Partner with data scientists, engineers, and stakeholders across the organisation to define high-impact solutions and deliver high-quality systems and data pipelines
• Building, training & iterating on data science, machine learning & artificial intelligence models
• Develop prototypes based on cutting-edge applied machine learning, working with different data modalities
• Own the technical translation of state-of-the-art machine learning innovations to inform the development of new product features
• Productionise and operate ML models and data pipelines at scale
• Design and implement well-defined APIs for new machine learning tools to make them available for customers and engineering teams across the organisation
• Design and implement machine learning infrastructure capabilities
• Reviewing and validating scalable data collection and processing methods
• Tracking and understanding emergent trends
• Sourcing and leveraging external research/data that strengthen our internal insights

• Video call with an internal recruiter (30 Mins)
• Interview with the Hiring Manager (1 hour)
• Technical Interview (1 hour)
• Cross Functional Interviews (30 mins x 2)