About the Job
This role is a hybrid position based in our London office (minimum 2x per month) open for candidates based in London or maximum 1,5h away from London.
Key Responsibilities
Our mission is to make data scientists more productive and to enable broader and deeper utilization of machine learning techniques to help improve business performance. As a Senior ML Ops Engineer, you will play a pivotal role in our dynamic team, collaborating closely with Data Science and Machine Learning experts. You will have the opportunity to learn many cutting edge technologies around Machine Learning Platform, as also push the boundaries, to test, develop and implement new ideas, technology and opportunities. Your primary responsibilities will include:
Empowering Data Science and ML teams, by providing the tools and infrastructure necessary for seamless execution of data science and machine learning tasks.
Support tech stack evolution, by developing across our existing technology stack while contributing to our migration into the AWS cloud, leveraging and adopting the latest services available in that environment.
Design, build and maintain a robust and scalable infrastructure to support pre-computed, batch and real-time model needs, ensuring smooth deployment and operation of machine learning models.
Foster a culture of innovation by generating and promoting new ideas within the ML Ops domain. Find creative solutions to complex problems, pushing the boundaries of what is possible.
Required Skills & Abilities
4+ years of ML Ops experience, focused on building modern ML infrastructure catering all stages of a model lifecycle, including development, deployment, management and monitoring.
Hands-on experience with AWS and GCP, demonstrating proficiency in leveraging cloud services for scalable and reliable ML Ops solutions.
Have a good grasp of IaC (Infrastructure-as-code) tools like Terraform and CloudFormation.
Previous exposure to additional technologies like Python, Spark, Pandas, Docker, Kubernetes, Seldon, MLFlow, Sagemaker, Valohai, ArgoCD, Argo Workflow, Postgres, BigQuery and Java is highly desirable.
Data Engineering experience on the Cloud preferably GCP or AWS
Ability to develop across a diverse technology stack and willingness and ability to take on new technologies.
Demonstrated experience participating on cross functional teams in fast-paced environments.
Excellent ability to break down complex problems into simple solutions.
Experience with CI/CD processes and platforms.
Ability to effectively operate both independently and as part of a team.
Sense of ownership, urgency and pride in your work.
High quality verbal and written communication skills
