Пропустити навігацію EPAM

Senior MLOps Engineer Manchester, UK

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Senior MLOps Engineer Description

Job #: 62607
Since 1993, EPAM Systems, Inc. (NYSE: EPAM) has leveraged its advanced software engineering heritage to become the foremost global digital transformation services provider – leading the industry in digital and physical product development and digital platform engineering services. Through its innovative strategy; integrated advisory, consulting, and design capabilities; and unique ‘Engineering DNA,’ EPAM’s globally deployed hybrid teams help make the future real for clients and communities around the world by powering better enterprise, education and health platforms that connect people, optimize experiences, and improve people’s lives. In 2021, EPAM was added to the S&P 500 and included among the list of Forbes Global 2000 companies.

Selected by Newsweek as a 2021 Most Loved Workplace, EPAM’s global multi-disciplinary teams serve customers in more than 45 countries across five continents. As a recognized leader, EPAM is listed among the top 15 companies in Information Technology Services on the Fortune 1000 and ranked as the top IT services company on Fortune’s 100 Fastest-Growing Companies list for the last three consecutive years. EPAM is also listed among Ad Age’s top 25 World’s Largest Agency Companies for three consecutive years, and Consulting Magazine named EPAM Continuum a top 20 Fastest-Growing Firm.

DESCRIPTION



You are a natural problem-solver who can navigate between traditional software development and machine learning implementations. You are motivated by the most exciting and innovative technologies and have expertise in building AI models and putting them into production.
If this sounds like you, this could be the perfect opportunity to join EPAM as a Senior AI Engineer. Scroll down to learn more about the position’s responsibilities and requirements.

What You’ll Do

  • Be part of the UK data function, supporting Data Science through the full ML life cycle to help take proof of concepts through to production
  • Automation of virtual infrastructure provisioning and Continuous Configuration Management processes
  • Automation of code delivery, release cycle configuration and CI/CD
  • Automation of rollout/management of container-based applications and systems
  • Building data science and business solutions leveraging functionality from cloud platforms
  • Applying best practice for cloud security and compliance
  • Delivering secured Big Data solutions for all types of data
  • Provide hands-on leadership, coaching and mentoring to junior members of staff
  • Work with data scientists, data engineers, software engineers and solution architects to develop end-to-end AI solutions
  • Use MLOps tools to validate, deploy and monitor models for example AzureML or MLflow or similar

What You Have

  • Proven track-record of deploying software products powered by ML using large commercial datasets and pipelines
  • Experience in partnering with business stakeholders to shape process optimization use cases powered by ML
  • Real world experience in applying MLOps; operating ML models in production
  • Good programming skills in Python and SQL (other programming languages are a bonus, e.g. R, SAS, Julia)
  • Good knowledge of one or more of the following: Azure Machine Learning, Google AI platform, Dataiku, Databrick's MLflow, Apache Spark
  • Some of the following:
    • Infrastructure as Code: Ansible, Terraform, Puppet
    • CI/CD: Jenkins, Gitlab
    • Containers: Jenkins, Kubernetes
    • AWS: EC2, EKS, Lambda, S3, SageMaker, ECS
    • Azure: AKS, Azure Functions, App Service, Cosmos DB, data Factory
    • GCP: Bigtable, Datastore, Deployment Manager, Compute engine
  • Solid experience building and optimizing big data pipelines, architectures and data sets
  • Algorithmic modelling of machine learning workloads
  • Solid experience with advanced analytics/ML modelling/visualization tools
  • Understanding the need for unit testing

We offer

  • We offer a range of benefits including
  • A competitive group pension plan, life assurance and income protection
  • Private medical insurance, private dental care and critical illness cover
  • Cycle scheme Tech scheme and season ticket loan
  • Employee assistance program
  • Various perks such as Gym discount, Friday lunch, on-site massage and regular social events
  • Unlimited access to LinkedIn learning solutions
  • EPAM Employee Stock Purchase Plan (ESPP) (subject to certain eligibility requirements)
  • Some of these benefits may be available only after you have passed your probationary period

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