Location:
Malvern, Pennsylvania (PA)
Contract Type: C2C
Posted: 1 month ago
Skills: AI , machine-learning or data engineering
Job Title: Lead AI/ML Engineer
Location: Malvern, PA
Position Type: Contract
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/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 stages 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.
Required Qualifications:
- Bachelor’s degree in a relevant field (master’s preferred).
- 7+ years of experience in AI engineering, machine-learning engineering or data engineering.
- Minimum 3 years of hands-on experience building ETL pipelines using AWS services.
- Proven experience developing and implementing ML pipelines for deploying, monitoring and managing AI/ML models in production.
- Proficient in Python and familiar with key machine-learning frameworks and libraries.
- Strong understanding of cloud technologies and AI/ML platforms such as 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.