Senior MLOps engineer

4 weeks ago

London, United Kingdom Definely Full time
Job Description

About Definely

Named in the top 25 of the prestigious Deloitte UK Technology Fast50 in 2023, as well as the EMEA Technology Fast 500, Definely is a fast-growing, venture-backed company transforming the $900bn global legal services market. Our customers include some of the world’s top law firms, financial institutions and multinational corporations such as Allen & Overy, Dentons and Deloitte. We are backed by prominent investors and VCs, including Octopus Ventures, Raine Ventures, Microsoft, Google for Startups and Nick Jenkins (founder of Moonpig and former Dragon).


About the Role

We are looking for a senior MLOps engineer to join our AI team. You will spearhead our MLOps strategy and implementation. You'll have the autonomy to shape and optimise our infrastructure, ensuring that we scale efficiently while maintaining robustness. This role carries significant responsibility, and we trust you to own critical decisions, from deployment strategies to cost optimisations. You'll work closely with our AI team to streamline model workflows and ensure seamless integration of cutting-edge AI products.


Your roles and responsibilities include the following:

  • Maintain and improve the MLOps platform allowing us to serve predictions at massive scale and iterate faster on all our models
  • Improve the MLOps platform in terms of processes, performance and testing
  • Research and experiment with the latest MLOps technologies and inference frameworks to unlock capabilities for all ML engineers in the company
  • Collaborate with data scientists, software engineers, and product managers to ensure smooth integration and deployment of ML models.
  • Set up monitoring and alerting systems to track the performance and health of ML models in production.


About You

  • Strong understanding of machine learning and natural language processing with relevant commercial experience in building and deploying Gen AI solutions.
  • Solid understanding of MLOps best practices with experience in designing and implementing CI/CD pipelines and deploying applications to AWS at scale.
  • Strong, fundamental technical expertise in cloud-native technologies, such as serverless functions, API gateway, container registry, Cloud Formation / CDK.
  • Professional experience of designing, building and managing bespoke MLOps in cloud environments, using tools such as SageMaker Processing, SageMaker Pipelines, Apache Airflow, and MLflow.
  • Good understanding of machine learning model development life cycle processes and tools: ML model development and experimentation, training pipelines, model serving and monitoring
  • Experience with monitoring, logging, and alerting systems (Grafana, Sentry).
  • Proactive in identifying problems, performance bottlenecks, and areas for improvement.
  • Take pride in building and operating scalable, reliable, and secure systems.
  • Strong collaboration and communication skills to work effectively with cross-functional teams and articulate technical concepts to non-technical stakeholders.


Nice to have

  • Strong Graph data modelling and database design experience.
  • experience with graph database like Neo4j
  • Experience in optimizing graph database performance and ensuring the scalability of graph-based solutions.


What we offer

  • Salary: £80-110K + bonus based on experience.
  • Private healthcare
  • An opportunity to be an integral part of a fast-growing startup as we move to scale-up
  • Work in a truly meritocratic organisation, alongside highly motivated individuals
  • A chance to work with some of the world’s leading law firms, financial institutions and multinational corporations
  • Office in the heart of London’s bustling Aldgate with the option to do hybrid working
  • Training and support
  • 25 days holiday per year excluding UK bank holidays
  • Pension
  • Flexible Working
  • Equipment

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