About this role: As a Senior ML Engineer you will take a leadership role in shaping the strategic direction of our machine learning infrastructure, proactively identifying opportunities for innovation and improvement.
You will drive the development of cutting-edge solutions that enhance the performance, scalability, and reliability of our machine learning systems. In collaboration with the Data Science team, you will ensure that models are deployed seamlessly, optimised for production environments, and meet the highest standards of efficiency and accuracy at scale.
You will also be responsible for architecting and overseeing the development of complex machine learning pipelines, managing both real-time and batch inference systems that are integral to our predictive platforms. You will work closely with cross-functional teams to anticipate future needs, recommending and implementing long-term solutions that align with our business objectives.
As a senior member of the team, you will mentor and guide mid-level Machine Learning Engineers, providing technical leadership and helping to shape best practices across the organisation. Your expertise will play a key role in conducting comprehensive code reviews, identifying areas for improvement, and fostering a culture of continuous learning and collaboration.
These are some of the key ingredients to the role: - As a senior member of the team, you will mentor and guide mid-level Machine Learning Engineers, providing technical leadership and helping to shape best practices across the organisation. Your expertise will play a key role in conducting comprehensive code reviews, identifying areas for improvement, and fostering a culture of continuous learning and collaboration.
- Beyond technical execution, you will be expected to communicate effectively with both technical and non-technical stakeholders, translating complex machine learning concepts into actionable business insights. You will present innovative solutions to key stakeholders, making compelling cases for new initiatives and guiding the strategic direction of our machine learning efforts.
- Finally, you will lead the integration of new technologies and tools into our infrastructure, staying ahead of industry trends and ensuring that our machine learning frameworks remain at the cutting edge of technological advancements.
What will you bring to the table?- Expert-level proficiency with cloud technologies (ideally AWS) and extensive experience with containerization and orchestration (preferably Kubernetes).
- Deep understanding of software development, DevOps, and MLOps best practices, with a proven track record of applying them in production.
- Extensive experience in designing, deploying, and maintaining scalable models and services in production environments.
- Strong understanding of Machine Learning, with the ability to collaborate deeply with Data Scientists on model deployment and optimization.
- Experience with MLflow for experiment tracking and model management, and Airflow or Dagster for orchestrating end-to-end ML pipelines and workflows.
- Significant experience with Data Engineering, Kafka, and stream processing.
- Proficiency in Python and SQL; or any other programming languages is a strong plus.
At JET, this is on the menu: Our teams forge connections internally and work with some of the best-known brands on the planet, giving us truly international impact in a dynamic environment.
Fun, fast-paced and supportive, the JET culture is about movement, growth and about celebrating every aspect of our JETers. Thanks to them we stay one step ahead of the competition.
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