MLOps & Gen AI - Senior/Lead
Experience: 7 to 13 years
Locations: Chennai, Bangalore, Hyderabad
As a Senior/Lead specializing in Generative AI and Machine Learning Engineering (MLE) , you will be at the forefront of AI innovation. You will design, deploy, and operationalize sophisticated models—including Large Language Models (LLMs) —to solve complex business challenges. Collaborating with cross-functional teams, you’ll deliver scalable, production-ready AI solutions that drive intelligent automation and spark creativity across industries.
Key Responsibilities:
Generative AI, NLP & MLE : Design, develop, deploy, and scale cutting-edge applications leveraging Generative AI models (e.g., GPT, LLa MA, Mistral), NLP techniques, and MLE/MLOps best practices.
Model Customization & Fine-Tuning : Fine-tune and customize LLMs using techniques like Lo RA and PEFT to create domain-specific, deployable models aligned with real-world business use cases.
ML Engineering & Deployment : Build and maintain end-to-end ML pipelines—including data preprocessing, model training, versioning, testing, and deployment—using MLflow, Docker, Kubernetes, and CI/CD methodologies.
Innovative Problem Solving : Apply advanced AI and ML methodologies to solve practical business problems, delivering measurable impact.
Scalable AI Solutions : Collaborate with platform and data engineering teams to ensure robust model deployment, monitoring, and retraining in production environments.
Data-Driven Insights : Analyze structured and unstructured data to uncover trends, optimize model performance, and guide strategic decisions.
Cross-Functional Collaboration : Partner with Consulting, Engineering, and Platform teams to integrate AI/ML solutions into enterprise architectures and business strategies.
Client Engagement : Interact directly with clients to understand requirements, present customized AI solutions, and advise on the adoption and operationalization of Generative AI and ML technologies.
Required Skills and Expertise:
Experience : Hands-on experience with real-world projects in Generative AI and Machine Learning Engineering (MLE/MLOps).
Generative AI Expertise : Deep expertise in designing and deploying LLM-based solutions using frameworks like Hugging Face, Lang Chain, Transformers, etc.
MLE & Production Readiness : Proven track record of building scalable, reliable, production-grade ML models and pipelines.
Deployment & Best Practices : Hands-on experience with containerization (Docker), orchestration (Kubernetes), model tracking (MLflow), and deployment on cloud platforms (AWS, GCP, Azure).
Development Proficiency : Strong coding skills in Python, with experience using web frameworks like Django or Flask.
API & Cloud Architecture : Deep understanding of APIs, microservices, and cloud-native deployment strategies.
Innovation & Curiosity : A strong passion for staying up to date with the latest advancements in Generative AI, LLMs, and ML engineering.
Communication : Ability to translate complex technical concepts into clear, business-focused insights and actionable recommendations.
