Job Description

Join our team as an

MLOps 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