

Jobs via Dice
ML / Data Engineer
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for an ML/Data Engineer in Reston, VA (Hybrid, 3 days onsite). Contract length is full-time, requiring 15+ years of experience, proficiency in AWS, Python, and MLflow, along with a Bachelor's degree in a related field.
🌎 - Country
United States
💱 - Currency
$ USD
-
💰 - Day rate
Unknown
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🗓️ - Date
February 26, 2026
🕒 - Duration
More than 6 months
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🏝️ - Location
Hybrid
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📄 - Contract
Fixed Term
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🔒 - Security
Unknown
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📍 - Location detailed
Reston, VA
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🧠 - Skills detailed
#Data Engineering #SageMaker #Airflow #Databases #ML Ops (Machine Learning Operations) #Python #Data Pipeline #Compliance #GIT #Spark (Apache Spark) #SQL (Structured Query Language) #Deployment #Data Lake #NoSQL #Model Validation #Computer Science #Monitoring #Data Science #Version Control #AWS (Amazon Web Services) #Scala #ML (Machine Learning) #Data Modeling #MLflow #Datasets
Role description
Dice is the leading career destination for tech experts at every stage of their careers. Our client, Hexaware Technologies, Inc, is seeking the following. Apply via Dice today!
Description:
ROLE: ML / Data Engineer / System Analyst / SME
Location- Reston, VA (Hybrid, 3 days onsite, 2 days offsite)
Duration- Full Time/contract
Note: Professional certification(s) desired 15+ years relevant experience is must
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
Focused on manipulating data in a software engineering capacity.
• Some of that data might live in relational systems, but its 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.
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:
• Bachelor's degree in computer science, Information Systems or related field
• Post-graduate degree desired
Dice is the leading career destination for tech experts at every stage of their careers. Our client, Hexaware Technologies, Inc, is seeking the following. Apply via Dice today!
Description:
ROLE: ML / Data Engineer / System Analyst / SME
Location- Reston, VA (Hybrid, 3 days onsite, 2 days offsite)
Duration- Full Time/contract
Note: Professional certification(s) desired 15+ years relevant experience is must
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
Focused on manipulating data in a software engineering capacity.
• Some of that data might live in relational systems, but its 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.
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:
• Bachelor's degree in computer science, Information Systems or related field
• Post-graduate degree desired






