MLOps Engineer

Join our team as anMLOps Engineer who acts as the critical bridge between Data Scientists and DevOps Engineers. Translate experimental ML models into scalable, production-ready applications using cutting-edge AWS services.

The Role

Core Responsibilities:

• Technical Liaison - Bridge Data Science and DevOps teams, ensuring effective AI/ML solution deployment
• Hands-On Support - Assist data scientists with DevOps issues, Docker containers, and MLOps tooling
• Model Deployment - Deploy Hugging Face Transformers and ML models as secure microservices
• AWS ML Platform - Build and evaluate models using SageMaker, Bedrock, Glue, Athena, and Redshift
• Knowledge Transfer - Create documentation and mentor teams on MLOps best practices
• Full ML Lifecycle - Manage training, validation, versioning, deployment, monitoring, and governance
• API Development - Develop secure APIs using Apigee for enterprise AI functionality access
• Automation - Build CI/CD pipelines using Jenkins and Maven for ML project integration

Essential Requirements

Minimum Qualifications:

• Degree in Computer Science, Data Science, Mathematics, Physics, or equivalent experience
• Python/R proficiency with practical ML and statistical modeling experience
• End-to-end ML delivery - From experimentation to production deployment
• Data science fundamentals - Data cleaning, feature engineering, model evaluation

Critical Technical Skills:

• Production ML deployment - Demonstrated experience maintaining AI/ML models in production
• AWS ML services - SageMaker, Bedrock, Glue, Kendra, Lambda, ECS Fargate, Redshift
• Hugging Face deployment - NLP, vision, and generative models in AWS environments
• API development - Flask, FastAPI microservices and REST API frameworks
• DevOps integration - CI/CD pipelines, Jenkins, Maven, Chef, Git version control
• Cloud architecture - Working across cloud-based infrastructures

Tech Stack & Tools

AWS Services: SageMaker, Bedrock, Glue, ECS Fargate, Athena, Kendra, RDS, Redshift, Lambda, CloudWatch
Development: Python, R, Flask, FastAPI, SQL
MLOps: Apigee, Hugging Face, Jenkins, Git, Docker
Environments: Jupyter, RStudio, Linux

What We're Looking For

Experience Level: Sr. Associate or Manager with hands-on data analytics and software delivery experience

Key Qualities:

• Client-facing skills - Strong communication, ability to explain technical concepts to non-technical stakeholders
• Multi-priority management - Handle competing priorities in challenging environments
• Continuous learning - Enthusiasm for new technologies, adaptability to client toolsets
• Collaborative mindset - Team player with trust, respect, courage, and openness
• Product-first attitude - Constantly improve product quality and support

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