Senior Machine Learning Engineer

We are seeking a skilled Senior Machine Learning Engineer to join our remote team. The successful applicant will play a substantial role in the design, development, and management of our ML pipeline, following industry-standard methodologies.
In this role, you will focus on constructing, deploying, maintaining, diagnosing, and enhancing steps within the ML pipeline. Furthermore, you will play a crucial role in leading and contributing to the design and deployment of ML prediction endpoints. Working in tandem with System Engineers to establish the ML lifecycle management environment and improve coding practices will be essential.
We invite those motivated by innovation to join our dynamic team!
The remote option applies only to the Candidates who will be working from any location in Ukraine.

#LI-DNI#LI-IRINABENKO

Responsibilities

• Contribution to the design, development, and management of an ML pipeline adhering to best practices
• Development, deployment, maintenance, troubleshooting, and enhancement of ML pipeline stages
• Leadership in designing and deploying ML prediction endpoints
• Collaboration with System Engineers to establish the ML lifecycle management setup
• Authoring specifications, documentation, and user guides for applications
• Enhancing coding practices and organizing repositories within the scientific workflow
• Configuring pipelines for various projects
• Continuous detection of technical risks and discrepancies, along with formulating mitigation plans
• Partnership with data scientists to operationalize predictive models, understanding the objectives and purposes of models developed by data scientists, and building scalable data preparation pipelines

Requirements

• 3+ years of programming experience, ideally in Python, alongside robust SQL knowledge
• Profound MLOps experience (e.g., Sagemaker, Vertex, Azure ML)
• Intermediate proficiency in Data Science, Data Engineering, and DevOps Engineering
• Showcase of at least one project delivered to production in an MLE role
• Expertise in Engineering Best Practices
• Practical experience in implementing Data Products using Apache Spark Ecosystem (Spark SQL, MLlib/SparkML) or alternative technologies
• Familiarity with Big Data technologies (e.g., Hadoop, Spark, Kafka, Cassandra, GCP BigQuery, AWS Redshift, Apache Beam, etc.)
• Experience with automated data pipeline and workflow management tools such as Airflow, Argo Workflow, etc
• Experience in different data processing paradigms such as batch, micro-batch, streaming
• Practical experience with at least one of the major Cloud Providers, including AWS, GCP, and Azure
• Production experience in integrating ML models into complex, data-driven systems
• Knowledge of DS using Tensorflow/PyTorch/XGBoost, NumPy, SciPy, Scikit-learn, Pandas, Keras, Spacy, HuggingFace, Transformers
• Experience with various types of databases including Relational, NoSQL, Graph, Document, Columnar, Time Series, etc

Nice to have

• Practical experience with Databricks MLOps-related tools or technologies such as MLFlow, Kubeflow, TensorFlow Extended (TFX)
• Experience with performance testing tools like JMeter or LoadRunner
• Familiarity with containerization technologies like Docker

We offer

• Work on a flexible schedule remotely or from any of our comfortable offices or coworking spaces in Ukraine
• Receive the necessary equipment to perform your work tasks
• Change projects and technology stacks within EPAM
• Gain experience in various business domains (Insurance, E-commerce, Healthcare, Finance, Travelling, Media, Artificial Intelligence, and more)
• Consider relocation options in over 30 countries worldwide
• Participate in volunteer, charity programs and communities (both technical and interest-based)
• You can plan your individual career path together with your manager
• Receive regular feedback from colleagues
• Improve your English for free with certified teachers (Speaking Clubs, client interview preparation courses, etc.)
• Get the opportunity to undergo free training and certification in AWS, GCP, or Azure Clouds
• Use the internal E-learn training program (18,200+ specialized training and mentoring programs)
• Access corporate accounts on LinkedIn Learning, Get Abstract and other partner resources
• Study at EPAM Solution Architecture School with the instructors who are practicing architects
• Develop as a leader, join Delivery Management, Resource Management, Leadership Essentials school and more
• Participate in internal communities (500+ meetups, technical discussions, brainstorming sessions, online events and conferences annually)
• Vacation and sick leave (including a sick leave without a medical certificate)
• A wide range of Voluntary Medical Insurance programs providing both medical treatment and various preventive options (including sports activities)
• Medical insurance for family members at corporate rates
• Company support during significant life events (childbirth or adoption, marriage, etc.)
• Support for psychological comfort: discounts on services from mental health specialists or coaches, thematic training
• E-kids program - a free programming language training program for EPAMers' children

EPAM strives to provide its global team of over 52,800+ professionals in more than 55 countries with opportunities for professional growth from day one of collaboration. Our colleagues are the source of EPAM's success, so we value cooperation, strive to always understand our clients' business and aim for the highest quality standards. No matter where you are, you will join a dedicated, diverse community that will help you realize your potential to the fullest.