FUSTIS LLC

Data Engineer with ML & AWS

⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Data Engineer with ML & AWS, based in hybrid Reston, Virginia, for 15 years. Pay rate is competitive. Requires strong AWS and ML engineering skills, proficiency in Python, and experience with Domino and SageMaker.
🌎 - Country
United States
πŸ’± - Currency
$ USD
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πŸ’° - Day rate
600
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πŸ—“οΈ - Date
February 26, 2026
πŸ•’ - Duration
Unknown
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🏝️ - Location
Hybrid
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πŸ“„ - Contract
W2 Contractor
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πŸ”’ - Security
Unknown
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πŸ“ - 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
Job Title- Data/Modelling Engineer Location: Hybrid Reston, Virginia(3 days onsite in every week)-Need Local Only Visa: USC/GC/GC-EAD Only for W2 & C2C open only for H1B visa not other Mode of Interview: In-Person Interview 15 years exp. Need One Manager reference not colleague or Lead with LinkedIn URL 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 β€’ Own the monitoring, tracking, and maintenance of ML models across Domino and SageMaker platforms. β€’ Implement MLflow for parameters, metrics, artifact management, and end to end lineage. β€’ Build and maintain scalable data pipelines for training, validation, and inference processes. β€’ Develop custom evaluation metrics, explainability components, and fairness/bias testing frameworks. β€’ Package models for deployment and support model lifecycle transitions across environments. β€’ Collaborate with data scientists, engineering teams, and governance stakeholders to ensure compliance and operational readiness. Required Skills & Experience β€’ Strong experience with AWS and ML engineering β€’ Proficiency in Python and MLflow β€’ Hands on expertise with Domino and SageMaker SDKs β€’ Experience with feature engineering and scalable data pipelines β€’ Knowledge of model validation, explainability, and bias/fairness tooling β€’ 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 itοΏ½s 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: 1. Bachelor degree in Computer Science, Information Systems or related field 1. Post-graduate degree desired 1. Professional certification(s) desired 15+ years relevant experience Best Regards, Jaideep Shastri Sr. Technical Recruiter || FUSTIS LLC 916-915-9898 (O) X 106 | 916-365-9533 (D) | jaideep.shastri@fustis.com