
Machine Learning Engineering Manager - Edinburgh
In this role you will:
- Scale existing ML models into production on a variety of cloud platforms
- Design, develop, test, and deploy data pipelines, machine learning infrastructure and client-facing products and services.
- Provide best-practice knowledge, reference architectures, and patterns for use across ML engineering and architecture communities
- Perform technical architecture assessments, analyse and resolve Analytics/ML related architectural problems
- Working closely with engineering, data science and operations teams to provide improvements and focus areas
- Communicate and provide guidance to senior client leadership and teams
- Contribute ML Engineering expertise to new sales activities
Who we are looking for:
We are looking for technical professionals from a variety of backgrounds with the willingness and ability to learn quickly, think creatively and drive complex ML Engineering problems to a solution.
We offer extensive opportunities for training and upskilling as part our technical career track, however, we’d typically expect experience in at least two of the following areas:
Hands-on experience in development, deployment and operation of data technologies and platforms such as:
- Cloud Services – AWS, GCP, Azure (and/or others)
- Data platforms – Big Data (e.g. Hadoop, Spark, Hive, Kafka), Data Warehouse (e.g. Teradata, Redshift, BigQuery, Snowflake), batch/streaming/low latency processing
- Platform Engineering – DevOps (Ansible, Jenkins, ELK), Containerisation (Docker, Kubernetes), Integration (APIs, microservices, ETL patterns)
- Experience in designing and managing key elements of a data and ML platforms: scalable data pipelines, feature stores, data warehouse, metadata, data quality, data security and encryption
- Experience in developing and architecting software across the full lifecycle from prototype to production.
- Experience in data and ML strategy, including analytics portfolio management (including experience in FinOps and Cloud operating model), use case design and definition, migration strategy etc
Additionally, we would love to see:
- Evidence of willingness and ability to learn quickly and the ability to apply creative thinking to find solutions and drive them to completion
- References to working in a multi-disciplinary team where you enjoyed being the technical expert and enabling others via collaborating as part of a community
- Business and commercial acumen and/or sales experience