Senior ML Ops Engineer

This job is with Skyscanner, an inclusive employer and a member of myGwork – the largest global platform for the LGBTQ+ business community. Please do not contact the recruiter directly.

Focused. Encouraging. Honest.

We need your expertise to help us do something great for our travellers: make booking stays and journeys more sustainable and straightforward. This involves technical challenges and the latest technology, from machine learning and cloud services to world-class APIs! At Skyscanner, we're revolutionizing the travel experience with cutting-edge AI and data-driven solutions. As a

Senior Engineer

in the Machine Learning Operations squad, you'll play a critical role in developing the infrastructure that empowers our data science teams to improve and deploy the models that are making an ever-greater contribution to our product experience. You'll typically be working in Java or Python, and with a technology stack that includes AWS, Kinesis, S3, Kubernetes, Spark, Airflow, gRPC, New Relic, Databricks, and more. This role requires expertise in distributed systems, microservices, and data pipelines, combined with a strong focus on observability and the ability to leverage vendor technologies to deliver impactful solutions. While this is not an ML development role, familiarity with the machine learning lifecycle is an advantage. Your ability to solve problems collaboratively with your teammates, and your passion to learn. You'll be able to break down problems into bite-size chunks and deliver them with high quality. Key Responsibilities Distributed Systems Development : Design and build scalable distributed systems using Java-based microservices and Python batch processing to support our ML models, evaluation, and observability.

Model Lifecycle : Create and maintain robust model deployment pipelines using PySpark and Databricks, ensuring efficient and reliable data flow across AI systems.

Vendor Integration : Identify and leverage vendor capabilities (e.g., AWS, Databricks, and other cloud services) to deliver high-quality solutions that align with organizational goals.

Observability Solutions : Develop monitoring and observability systems to track model performance, detect anomalies, and ensure outputs align with business and ethical standards.

Collaboration with Specialists : Work closely with cross-functional teams, including Security, Data Science and Product, to ensure comprehensive and secure solutions.

Knowledge Sharing : Act as a mentor and technical leader within the squad, fostering collaboration and growth among team members.

Complementary skills for this role Technical Expertise : Extensive experience with distributed systems engineering, including designing and implementing Java-based microservices and Python batch jobs.

Observability Knowledge : Deep understanding of observability principles, including monitoring, logging, and real-time system insights Data Engineering Skills : Proficiency in building data pipelines using PySpark and Databricks, with a strong understanding of data flow and processing.

Cloud Vendor Experience : Hands-on experience leveraging vendor technologies like AWS and Databricks to deliver scalable, robust solutions..

AI/ML Lifecycle Awareness : Familiarity with the machine learning lifecycle (e.g., tools like MLflow, Data Bricks Model Serving) and its integration into production systems.

Collaboration : Strong interpersonal skills with the ability to work effectively across teams, including specialists in security and data science.

Problem-Solving Skills : A proactive and innovative approach to tackling complex technical challenges.

Skyscanner is a hybrid working company and most roles can be either Full Time or Part Time. We believe when people meet regularly in person, we are better able to innovate, learn, collaborate and inspire. We ask people to be in the office on average 8 days per month. Already a global leader in travel, we want to elevate the way we work to a whole other level. In return, you'll get meaningful things like medical insurance, headspace subscriptions, a home office allowance, and the option to buy more holiday. You'll have the opportunity to work from any country for 4 weeks a year, and 30 days in our other global offices. Everything, in other words, to help you relax and give your best.For more details on Engineering at Skyscanner, check our Engineering Blog and follow Skyscanner Engineering on Twitter. #LI-DNI