Overview
Join to apply for the Lead Machine Learning Engineer role at EPAM Systems .
We are in search of a Lead Machine Learning Engineer who can join our remote team and propel innovation.
Your role will entail the design, development, and operation of the ML pipeline in line with industry best practices.
You will be responsible for the design, creation, maintenance, troubleshooting, and optimization of ML pipeline steps, and for designing and implementing ML prediction endpoints.
You will also work with System Engineers to set up the ML lifecycle management environment and to enhance coding practices.
We welcome those who are passionate about innovation to apply and join our team!
We accept CVs in English only.
Responsibilities
- Involvement in the design, development, and operation of the ML pipeline in accordance with best practices
- Design, creation, maintenance, troubleshooting, and optimization of ML pipeline steps
- Participation in the design and implementation of ML prediction endpoints
- Cooperation with System Engineers to set up the ML lifecycle management environment
- Creation of specifications, documentation, and user guides for developed applications
- Assistance in improving coding practices and repository organization within the science work cycle
- Establishment and configuration of pipelines for projects
- Continuous identification and mitigation of technical risks and gaps
- Partnership with data scientists to move predictive models into production, understand model scope and purpose, and create scalable data preparation pipelines
Requirements
- At least 5 years of experience in programming languages, ideally Python, with a strong understanding of SQL
- A proven history of leading and mentoring a team of engineers
- Intermediate proficiency in Data Science, Data Engineering, and DevOps Engineering
- History of at least one project delivered to production in an MLE role
- Expertise in Engineering Best Practices
- Hands-on experience with Data Products using the Apache Spark ecosystem or similar technologies
- Familiarity 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 (e.g., Airflow, Argo)
- Practical experience with at least one major Cloud Provider (AWS, GCP, or Azure)
- Production experience integrating ML models into complex data-driven systems
- DS experience with tools like TensorFlow, PyTorch, XGBoost, NumPy, SciPy, Scikit-learn, Pandas, Keras, SpaCy, HuggingFace, Transformers
- Experience with various database types (Relational, NoSQL, Graph, Document, Columnar, Time Series, etc.)
- Fluent English communication skills at a B2+ level
Nice to have
- Hands-on experience with Databricks MLOps-related tools (MLFlow, Kubeflow, TFX)
- Familiarity with performance testing tools (e.g., JMeter, LoadRunner)
- Understanding of containerization technologies like Docker
We offer
- Learning Culture – unlimited access to learning platforms and internal courses to support professional growth
- Health Coverage – premier health plan options for you and up to four family members
- Visual Benefit – up to $200,000 COP for visual health expenses
- Life Insurance – full-coverage life insurance plan
- Medical Leave Coverage – 100% coverage of medical leave for up to 90 days
- Professional Growth Opportunities – a comprehensive development process and tools for growth
- Stock Option Purchase Plan – opportunity to purchase stock at a reduced price
- Additional Income – opportunities to earn extra income through referrals, interviewing, and more
- Community Benefit – be part of a worldwide community of over 50,000 employees
EPAM is a leading global provider of digital platform engineering and development services.
We are committed to having a positive impact on our customers, employees, and communities.
We embrace a dynamic and inclusive culture, collaborate with multi-national teams, and offer opportunities to learn and grow across locations.
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