Data/Modeling Engineer V

Job Title: Machine Learning / Data Engineer

Location: Reston, VA (Hybrid – 3 Days Onsite, 2 Days Offsite)

Contact email: drishti@brillfy.com

Job Overview

We are seeking a highly skilled Machine Learning / Data Engineer to lead model development, experiment tracking, and end-to-end machine learning operations across Domino and Amazon SageMaker environments. The ideal candidate will drive model lifecycle quality, ensure governance alignment, and deliver engineering excellence through scalable data and ML solutions.

Key Responsibilities

Machine Learning & MLOps

• Own monitoring, tracking, and maintenance of ML models across Domino and Amazon SageMaker platforms

• Implement and manage MLflow for experiment tracking, including parameters, metrics, artifacts, and lineage

• Package models for deployment and manage lifecycle transitions across environments

• Develop custom evaluation metrics, explainability components, and fairness/bias testing frameworks

Data Engineering

• Build and maintain scalable data pipelines for training, validation, and inference

• Design, construct, and optimize datasets for analytical and business use cases

• Normalize databases and ensure data structures meet application requirements

• Integrate and transform raw data from multiple sources into machine-readable formats

Collaboration & Governance

• Collaborate with data scientists, engineers, and governance teams

• Ensure compliance with model governance and operational readiness standards

• Support version control and CI/CD practices using Git-based workflows

Required Skills & Experience

• Strong experience in AWS and machine learning engineering

• Proficiency in Python and MLflow

• Hands-on experience with Domino and Amazon SageMaker SDKs

• Expertise in feature engineering and scalable data pipelines

• Strong knowledge of SQL, data modeling, and data architecture

• Experience with big data tools such as Spark, Hive, and Airflow

• Familiarity with model validation, explainability, and bias/fairness tools

• Experience with Git, version control, and MLOps practices

Education & Experience

• Bachelor’s degree in Computer Science, Information Systems, or a related field (required)

• Postgraduate degree (preferred)

• Professional certifications (preferred)

• 15+ years of relevant experience