Machine Learning Engineer, Specialist
Hybrid · Malvern, Pennsylvania, United States
Job Summary
Machine Learning Engineer, Specialist responsible for developing and integrating ML algorithms into production systems. Key duties include designing and supporting data pipelines for model development, leveraging tools to build distributed data pipelines (e.g., PySpark, GlueETL), integrating model pipelines in production, contributing to SDLC/MDLC processes, reviewing and modifying data models and pipeline designs, documenting changes with data science teams, enabling data discovery and automated ingestion, analyzing raw data for quality, engaging stakeholders to translate business questions into analytic approaches, participating in planning and prioritization, and monitoring/model reliability through alerts. Strong Python (PySpark/PySQL) skills, AWS/Azure cloud experience, NoSQL familiarity, and experience with ML tooling and lifecycle concepts are required or strongly preferred.
Required Qualifications
- Minimum of 5 years of relevant work experience
- At least 3 years of hands-on experience designing ETL pipelines using AWS services (e.g., Glue, SageMaker)
- Proficiency in programming languages, particularly Python (including PySpark, PySQL)
- Familiarity with machine learning libraries and frameworks
- Strong understanding of cloud technologies, including AWS and Azure, and experience with NoSQL databases
- Experience with API design and development is a plus
- Solid understanding of software engineering principles, including design patterns, testing, security, and version control
- Knowledge of Machine Learning Development Lifecycle (MDLC) best practices and protocols
- Understanding of solution architecture for building end-to-end machine learning data pipelines
- Graduate degree preferred; undergraduate degree or equivalent experience accepted
- Sponsorship not offered for visa (Sponsorship restriction)
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