Machine Learning Operations Specialist

What role will you play in the team

You will serve as a specialized Machine Learning Operations Specialist, bridging the critical gap between data science model development and scalable production deployment. Your mission is to automate machine learning pipelines, optimize inference latency, and ensure high availability of our enterprise AI infrastructure across multiple cloud environments.

What you will do

You will architect and maintain end-to-end MLOps workflows using Apache Kafka and Apache Spark, integrate Large Language Models and RAG frameworks into production applications, deploy AI agents, and monitor containerized model services to ensure seamless operational continuity and high performance.

Key responsibility

• Design, implement, and maintain scalable ML pipelines utilizing Apache Spark and Apache Kafka for real-time streaming data.
• Deploy and manage Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) architectures in production.
• Configure and execute workflow automation tools including n8n, Flowise, and Zapier Automation for AI services.
• Optimize model training and inference workflows leveraging PyTorch, Keras, and advanced Prompt Engineering techniques.
• 
  Build and maintain robust ETL workflows using Talend and Apache Nifi to ensure data pipeline integrity.
• Establish monitoring systems for AI Agent Deployment to track system latency, accuracy, and resource utilization.

Required Qualification and Skills

• Master's or Bachelor's degree in Engineering, Computer Science, or Artificial Intelligence.
• Extensive practical experience in Python, APIs and webhooks, OpenAI API, and Claude API integration.
• Deep understanding of Machine Learning Frameworks such as PyTorch, TensorFlow, and Keras.
• Expertise in Big Data Technologies including Hadoop, Spark, and Apache Kafka.
• Familiarity with Database Management tools like MongoDB, PostgreSQL, and MySQL.
• Hands-on capability with ETL Tools like Informatica, Talend, and Apache Nifi.
• Strong knowledge of modern MLOps practices, containerization, and cloud deployment architectures.

Benefits Included

• Attractive compensation structure with annual increments and stock option grants.
• Robust health insurance, dental care, and critical illness coverage for employees and families.
• Flexible hybrid work arrangement options and ergonomic home office setup stipends.
• Dedicated annual budget for attending international AI and machine learning conferences.
• Unlimited access to premium online learning platforms and technical certification courses.
• Fully stocked pantry, wellness programs, and structured career mentorship initiatives.

A Day in the Life

You start your morning by reviewing automated alerts from production clusters running our LLM and RAG pipelines. Mid-morning involves debugging an Apache Kafka streaming issue and optimizing PyTorch inference scripts. Later, you collaborate with developers to integrate new API endpoints and refine prompt engineering templates for enterprise clients.