Overview

We are seeking an experienced Senior Machine Learning Engineer to join our team. The ideal candidate will take on leading roles in designing, developing, and optimizing our machine-learning platform. Your contributions will drive the success of our prediction models in real-world applications.

Responsibilities

  • Contribute to the design, development, and operational lifecycle of the ML pipeline based on best practices
  • Design, create, maintain, troubleshoot, and optimize ML pipeline steps
  • Own and contribute to the design and implementation of ML prediction endpoints
  • Collaborate with System Engineers to configure the ML lifecycle management environment
  • Write specifications, documentation, and user guides for developed applications
  • Promote improved coding practices and repository organization in the science work cycle
  • Establish and configure pipelines for projects
  • Identify technical risks and gaps, and devise mitigation strategies
  • Collaborate with data scientists to productionalize predictive models, understand the scope and purpose of the models built by data scientists, and create scalable data preparation pipelines

Requirements

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

Hungary

  • Dynamic, entrepreneurial corporate environment
  • Diverse multicultural, multi-functional, and multilingual work environment
  • Opportunities for personal and career growth in a progressive industry
  • Global scope, international projects
  • Widespread training and development opportunities
  • Unlimited access to LinkedIn learning solutions
  • Competitive salary and various benefits
  • Advanced wellbeing and CSR programs, recreation area

[epamgdo] Hungary (About EPAM)

EPAM is a leading global provider of digital platform engineering and development services. We are committed to having a positive impact on our customers, our employees, and our communities. We embrace a dynamic and inclusive culture. Here you will collaborate with multi-national teams, contribute to a myriad of innovative projects that deliver the most creative and cutting-edge solutions, and have an opportunity to continuously learn and grow. No matter where you are located, you will join a dedicated, creative, and diverse community that will help you discover your fullest potential.

[epamgdo] Hungary (Campus Programs)

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