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Lead ML/Data EngineerHallmark Global Solutions Ltd • United States
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Lead ML/Data Engineer

Hallmark Global Solutions Ltd
  • US
    United States
  • US
    United States
Apply Now

About

Dear All,
Our client is looking for Lead ML/Data Engineer - who is based out of
Reston, VA
This role is 3 Days Hybrid and 2 Days Remote Role
Overview We are seeking a highly skilled ML/Data Engineer to lead model development, experiment tracking, and end to end machine learning operations across Domino and Amazon SageMaker. This role will drive model lifecycle quality, governance alignment, and engineering excellence.
Responsibilities • Own the monitoring, tracking, and maintenance of ML models across Domino and SageMaker platforms. • Implement MLflow for parameters, metrics, artifact management, and end to end lineage. • Build and maintain scalable data pipelines for training, validation, and inference processes. • Develop custom evaluation metrics, explainability components, and fairness/bias testing frameworks. • Package models for deployment and support model lifecycle transitions across environments. • Collaborate with data scientists, engineering teams, and governance stakeholders to ensure compliance and operational readiness.
Required Skills & Experience • Strong experience with AWS and ML engineering • Proficiency in Python and MLflow • Hands on expertise with Domino and SageMaker SDKs • Experience with feature engineering and scalable data pipelines • Knowledge of model validation, explainability, and bias/fairness tooling • Familiarity with Git based workflows, version control, and MLOps practices
Skills:
This IT role requires a significant set of technical skills, including a deep knowledge of SQL, data modeling, and tools like Spark/Hive/Airflow.
Education/Work Exprerience:
1) Bachelor degree in Computer Science, Information Systems or related field
2) Post-graduate degree desired
3) Professional certification(s) desired 15+ years relevant experience
Focused on manipulating data in a software engineering capacity. Some of that data might live in relational systems, but it s increasingly moving towards NoSQL systems and data lakes. Normalize databases and ascertain the structure of the data meets the requirements of the applications that are accessing the information. Construct datasets that are easy to analyze and support company requirements. Combine raw information from different sources to create consistent and machine-readable formats.
  • United States

Languages

  • English
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