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Senior Machine Learning Engineer

AT EPAM Systems
EPAM Systems

Senior Machine Learning Engineer

Nurota, Uzbekistan

Are you a Senior Machine Learning Engineer passionate about making a significant impact in the tech industry?
We are seeking an individual with comprehensive knowledge in machine learning and data engineering who is ready to develop and implement groundbreaking models. In this role, you will work alongside diverse teams to engineer strategic solutions beyond machine learning. Our workspace champions innovation and offers a supportive environment that promotes growth.
If you thrive on solving complex problems and delivering impactful results, we encourage you to apply and join us.
Unlock the potential of remote work in Uzbekistan, giving you the flexibility to work from home or access our office in Tashkent.

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Responsibilities
  • Convert machine learning models and algorithm prototypes into production-ready optimized ML pipelines
  • Contribute to ML pipeline design and development, including validation and cold start problems, A/B tests, feedback loop, etc
  • Create and maintain ML pipeline steps
  • Optimize/tune ML models and ML pipelines to meet production environment requirements
  • Automate key parts of CI/CD pipelines for ML pipelines
  • Collaborate with data scientists to fine-tune and optimize models
  • Write specifications, documentation and user guides for developed solutions
  • Integrate ML models into existing software systems or create new applications
  • Allocate activities to junior ML engineers and bring tasks to closure
  • Improve coding practices, support code reviews and introduce best practices for model management
Requirements
  • 5 years of production experience working in an MLE role
  • At least one project delivered to production in an MLE role
  • Expertise in engineering best practices
  • Solid knowledge of Machine Learning fundamentals
  • Production background in integrating ML models into complex data-driven systems
  • Familiarity with the Python ML ecosystem
  • Proficiency in at least one major Cloud Provider such as AWS, GCP and Azure
  • Production experience with one of the MLOps-related platforms/technologies such as AWS SageMaker, Azure ML, GCP Vertex, Databricks MLFlow, Kubeflow or TensorFlow Extended
Nice to have
  • Competency in the Apache Spark Ecosystem
  • Expertise in LLM/GenAI
We offer
  • We connect like-minded people::
    • Delivering innovative solutions to industry leaders, making a global impact
    • Enjoyable working environment, whether it is the vibrant office or the comfort of your own home
    • Opportunity to work abroad for up to two months per year
    • Relocation opportunities within our offices in 55+ countries
    • Corporate and social events
  • We invest in your growth::
    • Leadership development, career advising, soft skills and well-being programs
    • Certifications, including GCP, Azure and AWS
    • Unlimited access to LinkedIn Learning, Get Abstract, O'Reilly, Cloud Guru
    • Free English classes with certified teachers
    • Discounts in local language schools, including offline courses for the Uzbek language
  • We cover it all::
    • Monetary bonuses for engaging in the referral program
    • Comprehensive medical & family care package
    • Four trust days per year (sick leave without a medical certificate)
    • Discounts for fitness clubs, dance schools and sports programs
    • Benefits package (sports activities, a variety of stores and services)
EPAM Uzbekistan is a team of technologists and innovators united by technology. In 2019, we opened our first office in Tashkent. Since then, we've built a continuously learning organization that helps its employees reach their full potential and achieve professional goals through learning. Our agile methodologies, client collaboration frameworks, engineering excellence programs, and hybrid teams offer many career paths and development opportunities.

Client-provided location(s): Uzbekistan
Job ID: EPAM-epamgdo_bltac22d0002d9cc10d_en-us_Other_Uzbekistan
Employment Type: Other