machine learning engineer

EPAM Systems is a global provider of digital platform engineering and software development services, helping clients transform their businesses through innovative technology solutions.

• Contribute to the design, development, and management of an ML pipeline aligned with best practices;
• Develop, deploy, maintain, troubleshoot, and improve ML pipeline components;
• Lead the design and deployment of ML prediction endpoints;
• Collaborate with System Engineers to create the ML lifecycle management framework;
• Write specifications, documentation, and user guides for applications;
• Improve coding practices and organize repositories within the scientific workflow;
• Set up pipelines for different projects;
• Identify technical risks and inconsistencies, proposing mitigation strategies;
• Work with data scientists to operationalize predictive models, ensuring clear understanding of model objectives and purposes, and develop scalable data preparation pipelines.

• 5+ Years of programming experience, with a focus on Python and strong SQL knowledge;
• Proficiency in MLOps tools and frameworks (e.g., Sagemaker, Vertex, Azure ML);
• Background in Data Science, Data Engineering, and DevOps Engineering at an intermediate level;
• Evidence of delivering at least one project in an MLE capacity;
• Expertise in Engineering Best Practices;
• Skills in utilizing the Apache Spark Ecosystem (Spark SQL, MLlib/SparkML) or equivalent technologies for Data Products;
• Familiarity with Big Data technologies (e.g., Hadoop, Spark, Kafka, Cassandra, GCP BigQuery, AWS Redshift, Apache Beam, etc.);
• Proficiency in working with automated data pipeline and workflow management tools such as Airflow or Argo Workflow;
• Understanding of various data processing paradigms, including batch, micro-batch, and streaming;
• Experience with at least one major Cloud Provider, such as AWS, GCP, or Azure;
• Production familiarity with integrating ML models into complex, data-intensive systems;
• Knowledge of DS technologies such as Tensorflow, PyTorch, XGBoost, NumPy, SciPy, Scikit-learn, Pandas, Keras, Spacy, HuggingFace, Transformers;
• Competency in working with multiple database types, including Relational, NoSQL, Graph, Document, Columnar, Time Series, etc;
• Nice to have: background in Databricks MLOps-related tools or technologies including MLFlow, Kubeflow, and TensorFlow Extended (TFX), proficiency in performance testing tools such as JMeter or LoadRunner, understanding of containerization technologies like Docker.

• Work on a flexible schedule remotely or from any comfortable office or coworking space in Ukraine;
• Receive necessary equipment to perform work tasks;
• Change projects and technology stacks within EPAM;
• Gain experience in various business domains including Insurance, E-commerce, Healthcare, Finance, Travelling, Media, and Artificial Intelligence;
• Relocation opportunities may be available for eligible candidates depending on the role and openings at other EPAM locations;
• Participate in volunteer, charity programs, and communities;
• Plan individual career path and receive regular feedback from colleagues;
• Improve English for free with certified teachers through Speaking Clubs and client interview preparation courses;
• Get free training and certification in AWS, GCP, or Azure Clouds;
• Use internal E-learn training program and corporate accounts on LinkedIn Learning and Get Abstract;
• Study at EPAM Solution Architecture School with practicing architects;
• Develop as a leader and participate in internal communities and meetups;
• Vacation and sick leave including sick leave without a medical certificate;
• Voluntary Medical Insurance programs providing medical treatment and preventive options including sports activities;
• Medical insurance for family members at corporate rates;
• Company support during significant life events;
• Support for psychological comfort with discounts on services from mental health specialists or coaches and thematic training;
• Access to the E-kids program for employees' children.