LLMOps Engineer

HCLTech is hiring for LLMOps - Virtual Drive | 5th Feb 2025 Registration Link - Experienced Required - 11 to 15 Years Notice Period - Immediate to 30 Days The job opportunity is based exclusively in Noida only. About Us HCLTech AI & Cloud Native Labs is the global Centre of Excellence guiding the application of advanced technologies and leading the way for clients and HCL employees worldwide. We engage with the world’s largest enterprises for strategic advice, accelerated engineering, and industry thought leadership to guide their modernization and transformation outcomes. As industry leaders in cloud-enabled transformation, we sponsor industry bodies like the Cloud Native Computing Foundation (CNCF) and contribute to successfully deploying emerging technologies Job Description & Requirements Position Summary LLMOps (Large language model operations) Engineer will play a pivotal role in building and maintaining the infrastructure and pipelines for our cutting-edge Generative AI applications , establishing efficient and scalable systems for LLM research, evaluation, training, and fine-tuning. Engineer will be responsible for managing and optimizing large language models (LLMs) across various platforms This position is uniquely tailored for those who excel in crafting pipelines, cloud infrastructure, environments, and workflows. Your expertise in automating and streamlining the ML lifecycle will be instrumental in ensuring the efficiency, scalability, and reliability of our Generative AI models and associated platform. LLMOps engineer’s expertise will ensure the smooth deployment, maintenance, and performance of these AI platforms and powerful large language models. You will follow Site Reliability Engineering & MLOps principles and will be encouraged to contribute your own best practices and ideas to our ways of working. Reporting to the Head of Cloud Native operations, you will be an experienced thought leader, and comfortable engaging senior managers and technologists. You will engage with clients, display technical leadership, and guide the creation of efficient and complex products/solutions. Key Responsibilities • Contribute to the technical delivery of projects, ensuring a high quality of work that adheres to best practices, brings innovative approaches and meets client expectations. Project types include following (but not limited to): * Solution architecture, Proof of concepts (PoCs), MVP, design, develop, and implementation of ML/LLM pipelines for generative AI models, encompassing data ingestion, pre-processing, training, deployment, and monitoring. * Automate ML tasks across the model lifecycle. • Contribute to HCL thought leadership across the Cloud Native domain with an expert understanding of advanced AI solutions using Large Language Models (LLM) & Natural Language Processing (NLP) techniques and partner technologies. • Collaborate with cross-functional teams to integrate LLM and NLP technologies into existing systems. • Ensure the highest levels of security and compliance are maintained in all ML and LLM operations. • Stay abreast of the latest developments in ML and LLM technologies and methodologies, integrating these innovations to enhance operational efficiency and model effectiveness. • Collaborate with global peers from partner ecosystems on joint technical projects. This partner ecosystem includes Google, Microsoft, AWS, IBM, Red Hat, Intel, Cisco, and Dell / VMware etc. Mandatory Skills & Experience • Expertise in designing and optimizing machine-learning operations, with a preference for LLMOps. • Proficient in Data Science, Machine Learning, Python, SQL, Linux/Unix shell scripting. • Experience on Large Language Models and Natural Language Processing (NLP), and experience with researching, training, and fine-tuning LLMs. Contribute towards fine-tune Transformer models for optimal performance in NLP tasks, if required. • Implement and maintain automated testing and deployment processes for machine learning models w.r.t LLMOps. • Implement version control, CI/CD pipelines, and containerization techniques to streamline ML and LLM workflows. • Develop and maintain robust monitoring and alerting systems for generative AI models ensuring proactive identification and resolution of issues. • Research or engineering experience in deep learning with one or more of the following: generative models, segmentation, object detection, classification, model optimizations. • Experience implementing RAG frameworks as part of available-ready products. • Experience in setting up the infrastructure for the latest technology such as Kubernetes, Serverless, Containers, Microservices etc. • Experience in scripting / programming to automate deployments and testing, worked on tools like Terraform and Ansible. Scripting languages like Python, bash, YAML etc. • Experience on CI/CD opensource and enterprise tool sets such as Argo CD, Jenkins (others like Jenkins X, Circle CI, Argo CD, Tekton, Travis, Concourse an advantage). • Experience with the GitHub/DevOps Lifecycle • Experience in Observability solutions (Prometheus, EFK stacks, ELK stacks, Grafana, Dynatrace, AppDynamics) • Experience in at-least one of the clouds for example - Azure/AWS/GCP • Significant experience on microservices-based, container-based or similar modern approaches of applications and workloads. • You have exemplary verbal and written communication skills (English). Able to interact and influence at the highest level, you will be a confident presenter and speaker, able to command the respect of your audience Client Relationships • Advise on best practices related to platform & Operations engineering and cloud native operations, run client briefings and workshops, and engage technical leaders in a strategic dialogue. • Develop and maintain strong relationships with client stakeholders. • Perform a Trusted Advisor role. • Contribute to technical projects with a strong focus on technical excellence and on-time delivery