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Lead Machine Learning Engineer Cambridge, UK

Lead Machine Learning Engineer Description

Job #: 82778
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. Selected by Newsweek as a 2021 Most Loved Workplace, EPAM’s global multi-disciplinary teams serve customers in more than 40 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 and in 2020, Consulting Magazine named EPAM Continuum a top 20 Fastest-Growing Firm.

DESCRIPTION



EPAM is looking for a hands-on Lead Machine Learning Engineer to be part of the continued acceleration to strengthen our business in Western Europe.
We do not believe in collecting data without purpose. Analysis by seasoned experts can bring actionable information to organizations when they need it most. Whether our clients are looking to make better decisions for business development or create platforms and solutions that utilize data to streamline and improve operations—we are data-driven, business outcome oriented and we want to help our clients and partners by delivering innovative solutions to their most challenging problems.

What You’ll Do

  • Be responsible for the transition of machine learning algorithms to production environment and integration with enterprise ecosystem
  • Design, create, maintain, troubleshoot, and optimize the complete end-to-end machine learning life cycle
  • Write specifications, documentation, and user guides for developed solutions
  • Build frameworks for data scientists to accelerate the development of production-grade machine learning models
  • Collaborate with data scientists and engineering team to optimize the performance of ML pipeline
  • Constant improvement of SDLC practices
  • Exploration of new tools and techniques and propose improvements
  • Establish and configure CI/CD/CT processes
  • Design and maintain ML models continuous training
  • Provide capabilities for early detection of various drifts (data, concept, schema., etc,)
  • Promote and support MLOps practices
  • Continuously identify technical risks and gaps, devise mitigation strategies
  • Identify and eliminate technical debt in machine learning systems

What You Have

  • 5+ years of different backend experience (any of Java, C#, Python, etc)
  • 1+ years of experience building and working on search systems based on Elasticsearch, Solr, Lucene, Coveo, Vespa, etc
  • Understanding of query lifecycles, ingestion of the data. Knowledge of different built-in capabilities of those engines

Nice to have

  • Understanding of the cluster sizing, how to write custom plugins for Solr & Elasticsearch
  • Experience working with ETL tools such as Logstash, Talend, AWS Glue or similar
  • NLP experience (spacy, nltk, word2vec, etc)
  • Experience in different business domains (e-commerce, publishing, finance, etc.)

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
  • Unlimited access to LinkedIn learning solutions
  • EPAM Employee Stock Purchase Plan (ESPP) (subject to certain eligibility requirements)
  • Various perks such as Gym discount, Friday lunch, on-site massage and regular social events
  • Some of these benefits may be available only after you have passed your probationary period

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