Senior MLOps Engineer

2 weeks ago

Oxford, United Kingdom Oxa Autonomy Full time

Your Role

:

As a Senior MLOps Engineer you will be responsible for designing and building cloud solutions to support the activities of machine learning engineers across the company. You will build tools and APIs to support ML teams in every stage of their ML workflows. You will champion automation of the entire ML lifecycle, covering data ingestion, model development, model training, model management, deployment, serving and monitoring.

On a day to day basis you will prototype tools and APIs to allow ML engineers to access cloud based infrastructure developed by your MLOps colleagues, iterating towards a production-ready service. In developing solutions you will carefully consider the skillset of the end user and design and document tools accordingly. ML team members will come to you as the authority regarding MLOps best practices and you will provide training in the use of in-house and third-party MLOps tools.

In addition to supporting ML teams with their custom MLOps requirements, you will form part of the MLOps platform team and contribute core infrastructure.

Requirements

What you need to succeed:

Bachelor's or Master's degree in STEM subject with a focus on software engineering or equivalent experience. Deep understanding of software development practices. Experience designing python APIs. Experience working with ML engineers and data scientists or a basic understanding of ML principles and frameworks. Cloud platform experience. Approachable and able to play an intra- and inter-team supporting role. Excellent listening skills and proven experience of seeking feedback from internal or external stakeholders to improve technical solutions. Hands-on experience using typical DevOps technologies linux, python, bash, docker, kubernetes, jenkins

Extra Kudos if you have

Previous role as an MLOps engineer Use of ML frameworks pytorch, tensorflow Familiarity with MLOps platforms Kubeflow, MLFlow, Tensorflow Extended, ClearML, VertexAI, Amazon SageMaker Experience deploying ML models in production environments

Benefits

We provide:

Competitive salary, benchmarked against the market and reviewed annually Hybrid and/or flexible work arrangements An outstanding £2,000 flexible benefits including private medical insurance, critical illness coverage, life assurance, EAP, group income protection A salary exchange pension plan 25 days’ annual leave plus bank holidays A pet-friendly office environment Safe assigned spaces for team members with individual and diverse needs

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