MLOps Engineer

Bright Vision Technologies•Bridgewater, NJ

20h•Remote

About The Position

MLOps Engineer Bright Vision Technologies is a forward-thinking software development company dedicated to building innovative solutions that help businesses automate and optimize their operations. We leverage cutting-edge cloud data platform technologies to design scalable, secure, and high-performance analytics environments. As we continue to grow, we’re looking for a skilled MLOps Engineer to join our dynamic team and contribute to our mission of transforming business processes through technology. This is a fantastic opportunity to join an established and well-respected organization offering tremendous career growth potential. Company: Bright Vision Technologies ( www.bvteck.com ) Job Title: MLOps Engineer Job Location: Bridgewater, New Jersey - 08807 Onsite/Hybrid: Remote FULL-TIME ROLE WITH BRIGHT VISION Job Description: Architect and implement MLOps platforms to streamline Machine Learning Pipelines, from experimentation to production deployment. Build scalable Model Deployment & Monitoring solutions using Python, TensorFlow, and PyTorch, ensuring real-time inference and drift detection. Leverage MLflow for experiment tracking, model registry, and lifecycle management across diverse ML workflows. Design and manage Feature Stores for efficient feature engineering, serving, and versioning to accelerate model development. Automate CI/CD pipelines with Git, Docker containerization, and Kubernetes orchestration for seamless model updates and rollbacks. Provision cloud-native infrastructure on AWS, Azure, or GCP using Infrastructure as Code (Terraform) for reproducible ML environments. Implement Data Versioning practices (e.g., DVC) alongside model artifacts to maintain reproducibility and auditability. Optimize Linux-based systems for high-performance ML operations, including GPU/TPU resource management. Collaborate in Agile methodologies, driving iterative delivery of MLOps features through sprints and stakeholder alignment. Monitor and scale production ML systems, proactively addressing performance issues, cost optimization, and compliance needs. Position offered by “No Fee agency.” Equal Employment Opportunity (EEO) Statement Bright Vision Technologies (BV Teck) is committed to equal employment opportunity (EEO) for all employees and applicants without regard to race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, veteran status, or any other protected status as defined by applicable federal, state, or local laws. This commitment extends to all aspects of employment, including recruitment, hiring, training, compensation, promotion, transfer, leaves of absence, termination, layoffs, and recall. BV Teck expressly prohibits any form of workplace harassment or discrimination. Any improper interference with employees' ability to perform their job duties may result in disciplinary action up to and including termination of employment. Equal Employment Opportunity (EEO) Statement Bright Vision Technologies (BV Teck) is committed to equal employment opportunity (EEO) for all employees and applicants without regard to race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, veteran status, or any other protected status as defined by applicable federal, state, or local laws. This commitment extends to all aspects of employment, including recruitment, hiring, training, compensation, promotion, transfer, leaves of absence, termination, layoffs, and recall. BV Teck expressly prohibits any form of workplace harassment or discrimination. Any improper interference with employees' ability to perform their job duties may result in disciplinary action up to and including termination of employment.

Responsibilities

Architect and implement MLOps platforms to streamline Machine Learning Pipelines, from experimentation to production deployment.
Build scalable Model Deployment & Monitoring solutions using Python, TensorFlow, and PyTorch, ensuring real-time inference and drift detection.
Leverage MLflow for experiment tracking, model registry, and lifecycle management across diverse ML workflows.
Design and manage Feature Stores for efficient feature engineering, serving, and versioning to accelerate model development.
Automate CI/CD pipelines with Git, Docker containerization, and Kubernetes orchestration for seamless model updates and rollbacks.
Provision cloud-native infrastructure on AWS, Azure, or GCP using Infrastructure as Code (Terraform) for reproducible ML environments.
Implement Data Versioning practices (e.g., DVC) alongside model artifacts to maintain reproducibility and auditability.
Optimize Linux-based systems for high-performance ML operations, including GPU/TPU resource management.
Collaborate in Agile methodologies, driving iterative delivery of MLOps features through sprints and stakeholder alignment.
Monitor and scale production ML systems, proactively addressing performance issues, cost optimization, and compliance needs.