Role: Senior ML Engineer

Location: Malvern, PA - hybrid onsite

Responsibilities

- Design develop and optimize complex data pipelines using machine learning engineering best practices to ensure scalability efficiency and reliability

- Develop and implement robust MLOPS pipelines to support the deployment monitoring and lifecycle management of AI or ML models in production environments.

- Integrate and maintain data and model pipelines proactively diagnosing data quality issues and documenting assumptions.

- Collaborate closely with data scientists to validate model ready datasets and ensure thorough accurate feature documentation.

- Conduct exploratory data analysis and discovery on raw data sources incorporating business context to support model development.

- Track data lineage and perform root cause analysis during early-stage of exploration or issue resolution.

- Partner with internal stakeholders to understand business processes and translate them into scalable analytical solutions.

- Develop and maintain model monitoring scripts, investigate alerts and coordinate timely resolution.

- Bachelors degree in a relevant field required masters degree preferred7 plus years of relevant experience in AI engineering or machine learning engineering or data engineering experience

- Minimum 3 plus years of hands-on experience building ETL pipelines using AWS services

- Proven experience developing and implementing MLs pipeline for deploying monitoring and managing AI or ML models in production.

- Proficient in Python And familiar with key machine learning frameworks and libraries

- Strong understanding of cloud technologies and AI or ML platforms like AWS SageMaker.

- Solid grasp of software engineering principles including design patterns testing security and version control.

- Knowledge of the machine learning development life cycle (MDLC) and AI engineering best practices

- Experience designing and implementing end to end machine learning pipelines and solution architectures