Senior Machine Learning Engineer
Company
EPAM Systems
Location
Kardítsa, Greece
Type
Full Time
Job Description
We are in search of a Senior Machine Learning Engineer to be part of our team. The selected candidate will contribute significantly to the design, development, and operation of our ML pipeline, guided by industry best practices.
Your responsibility will revolve around designing, creating, maintaining, troubleshooting, and optimizing ML pipeline steps. You will also be instrumental in owning and contributing to the design and implementation of ML prediction endpoints. Close collaboration will be required with System Engineers to set up the ML lifecycle management environment and support the enhancement of coding practices.
We welcome those driven by a spirit of innovation to apply and become a vital part of our team!
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The remote option applies only to the Candidates who will be working from any location in Greece.
#LI-DNI#LI-IRINABENKO
Responsibilities
- Contribution to the design, development, and operation of ML pipeline based on best practices
- Design, creation, maintenance, troubleshooting, and optimization of ML pipeline steps
- Ownership and contribution to the design and implementation of ML prediction endpoints
- Cooperation with System Engineers to set up the ML lifecycle management environment
- Writing of specifications, documentation, and user guides for developed applications
- Support for the enhancement of coding practices and repository organization in the science work cycle
- Establishment and configuration of pipelines for projects
- Continuous identification of technical risks and gaps, and devising of mitigation strategies
- Collaboration with data scientists to bring predictive models into production, understanding the scope and purpose of the models built by data scientists and creating scalable data preparation pipelines
- 3+ years of experience in programming languages, ideally Python, with strong SQL knowledge
- Profound MLOps experience (Sagemaker, Vertex, or Azure ML)
- Intermediate proficiency in Data Science, Data Engineering, and DevOps Engineering
- At least one project delivered to production in an MLE role
- Expertise in Engineering Best Practices
- Practical experience implementing Data Products using the 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, i.e., Airflow, Argo Workflow, etc
- Experience in different data processing paradigms (batch, micro-batch, streaming)
- Practical experience working with at least one of the major Cloud Providers such as AWS, GCP, and Azure
- Production experience integrating ML models into complex data-driven systems
- DS knowledge 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.)
- Practical experience with Databricks MLOps-related tools/technologies like MLFlow, Kubeflow, TensorFlow Extended (TFX)
- Experience with performance testing tools like JMeter or LoadRunner
- Familiarity with containerization technologies like Docker
- For you:
- Paid annual vacation
- Paid sick leave days
- Private health insurance
- Stable income
- Meal and home office compensation
- For your comfortable work:
- Remote and hybrid work opportunities
- Corporate laptop
- Possibility to work on your own device
- Free licensed software
- Relocation opportunities
- Free wellbeing activities
- For your growth:
- Possibility to create a Personal Development Plan from the first day in the company
- Free trainings for technical and soft skills
- Free access to LinkedIn Learning platform
- Free access to internal and external e-Libraries
- Certification opportunities
- Language courses
- Internal technical and non-technical communities
- Possibility to contribute in internal, opensource products
EPAM is committed to providing our global team of 52,800+ EPAMers with inspiring careers. EPAMers lead with passion and honesty and think creatively. Our people are the source of our success, and we value collaboration, try always to understand our customers' business, and strive for the highest standards of excellence.
Date Posted
12/24/2024
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