Job Title: Lead MLOps Engineer

Location: Hyderabad, India

Summary:

We are seeking a highly motivated and experienced Lead MLOps Engineer to join our team and lead the development and operation of our Machine Learning Operations (MLOps) infrastructure. You will be responsible for building robust, scalable, and automated pipelines for deploying, monitoring, and managing our AI/ML models, with a particular focus on Conversational AI, RAG, NLP & LLM systems. This role requires a strong blend of technical expertise in MLOps principles, DevOps practices, and cloud technologies.

Responsibilities:

• Pipeline Design & Development: Architect, build, and maintain end-to-end CI/CD pipelines for the deployment and operation of AI/ML models, specifically focusing on Conversational AI, RAG (Retrieval Augmented Generation), NLP (Natural Language Processing), and LLM (Large Language Model) systems.
• Infrastructure Management: Design and manage the underlying infrastructure required to support our MLOps workflows, including Kubernetes clusters, containerized environments, and cloud resources.
• Model Deployment & Monitoring: Implement robust model deployment strategies and monitoring solutions to ensure high availability, performance, and accuracy of deployed models.
• DevOps Practices: Champion DevOps best practices throughout the ML lifecycle, fostering a culture of automation, collaboration, and continuous improvement.
• Cloud Platform Expertise: Leverage cloud platforms (AWS, Azure, GCP) to build scalable and cost-effective MLOps solutions.
• Collaboration & Mentorship: Collaborate closely with data scientists, machine learning engineers, and software developers to ensure seamless integration of ML models into production environments. Mentor junior engineers in MLOps best practices.
• Performance Optimization: Identify and implement optimizations to improve the efficiency and performance of our MLOps pipelines and deployed models.
• Security & Compliance: Ensure that all MLOps processes and infrastructure adhere to security and compliance requirements.

Qualifications:

• Education: Bachelor’s degree in Computer Science or equivalent degree with a strong foundation in AI/ML Operations and Data Science operations.
• Experience: 7+ years of overall experience in software development, with a focus on MLOps principles and practices.
• Containerization & Orchestration: Extensive experience with containerization technologies (Docker) and orchestration platforms (Kubernetes).
• DevOps Expertise: Strong skills with DevOps practices and CI/CD pipelines (e.g., Jenkins, GitLab CI, Azure DevOps).
• Cloud Proficiency: Proven experience working with cloud platforms and tools including Linux, Git, Docker, Terraform, Kubernetes, AWS, Azure, or GCP.
• ML Model Deployment & Monitoring: Experience with model deployment and monitoring tools and techniques.
• Programming Skills: Proficient in Linux shell scripting, Jenkins, Terraform, Ansible, Python.