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LLM Ops Engineer
2 months ago
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, andcomfortable engaging senior managers and technologists. You will engage with clients, displaytechnical leadership, and guide the creation of efficient and complex products/solutions.
Key ResponsibilitiesTechnical & Architectural Leadership• Contribute to the technical delivery of projects, ensuring a high quality of work that adheres tobest practices, brings innovative approaches and meets client expectations. Project types includefollowing (but not limited to):o Solution architecture, Proof of concepts (PoCs), MVP, design, develop, andimplementation of ML/LLM pipelines for generative AI models, encompassing dataingestion, pre-processing, training, deployment, and monitoring.o Automate ML tasks across the model lifecycle.• Contribute to HCL thought leadership across the Cloud Native domain with an expertunderstanding of advanced AI solutions using Large Language Models (LLM) & Natural LanguageProcessing (NLP) techniques and partner technologies.• Collaborate with cross-functional teams to integrate LLM and NLP technologies into existingsystems.• Ensure the highest levels of security and compliance are maintained in all ML and LLMoperations.• 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 partnerecosystem includes Google, Microsoft, AWS, IBM, Red Hat, Intel, Cisco, and Dell / VMware etc.Service Delivery• Provide a technical hands-on contribution. Create scalable infra to support enterprise loads(distributed GPU compute, foundation models, orchestrating across multiple cloud vendors, etc.)• Ensuring the reliable and efficient platform operations.• Apply data science, machine learning, deep learning, and natural language processing methodsto analyse, process, and improve the model’s data and performance.• Create and optimize prompts and queries for retrieval augmented generation and promptengineering techniques to enhance the model’s capabilities and user experience w.r.tOperations & associated platforms.• Client-facing influence and guidance, engaging in consultative client discussions and performinga Trusted Advisor role.• Provide effective support to HCL Sales and Delivery teams.• Support sales pursuits and enable HCL revenue growth.• Define the modernization strategy for client platform and associated IT practices, create solutionarchitecture and provide oversight of the client journey.Innovation & Initiative• Always maintain hands-on technical credibility, keep in front of the industry, and be prepared toshow and lead the way forward to others.• Engage in technical innovation and support HCL’s position as an industry leader.• Actively contribute to HCL sponsorship of leading industry bodies such as the CNCF and LinuxFoundation.• Contribute to thought leadership by writing Whitepapers, blogs, and speaking at industry events.• Be a trusted, knowledgeable internal innovator driving success across our global workforce.Client Relationships• Advise on best practices related to platform & Operations engineering and cloud nativeoperations, run client briefings and workshops, and engage technical leaders in a strategicdialogue.• 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-timedelivery.
Mandatory Skills & Experience• Expertise in designing and optimizing machine-learning operations, with a preference forLLMOps.• Proficient in Data Science, Machine Learning, Python, SQL, Linux/Unix shell scripting.• Experience on Large Language Models and Natural Language Processing (NLP), and experiencewith researching, training, and fine-tuning LLMs. Contribute towards fine-tune Transformermodels for optimal performance in NLP tasks, if required.• Implement and maintain automated testing and deployment processes for machine learningmodels w.r.t LLMOps.• Implement version control, CI/CD pipelines, and containerization techniques to streamline MLand LLM workflows.• Develop and maintain robust monitoring and alerting systems for generative AI models ensuringproactive 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 optimisations.• 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 toolslike 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 likeJenkins 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 ofapplications and workloads.• You have exemplary verbal and written communication skills (English). Able to interact andinfluence at the highest level, you will be a confident presenter and speaker, able to commandthe respect of your audience.
Desired Skills & Experience• Bachelor level technical degree or equivalent experience; Computer Science, Data Science, orEngineering background preferred; Master’s Degree desired.• Experience in LLMOps or related areas, such as DevOps, data engineering, or ML infrastructure.• Hands-on experience in deploying and managing machine learning and large language modelpipelines in cloud platforms (e.g., AWS, Azure) for ML workloads.• Familiar with data science, machine learning, deep learning, and natural language processingconcepts, tools, and libraries such as Python, TensorFlow, PyTorch, NLTK etc.• Experience in using retrieval augmented generation and prompt engineering techniques toimprove the model’s quality and diversity to improve operations efficiency. Proven experiencein developing and fine-tuning Language Models (LLMs).• Stay up-to-date with the latest advancements in Generative AI, conduct research, and exploreinnovative techniques to improve model quality and efficiency.• The perfect candidate will already be working within a System Integrator, Consulting orEnterprise organisation with 8+ years of experience in a technical role within the Cloud domain.• Deep understanding of core practices including SRE, Agile, Scrum, XP and Domain Driven Design.Familiarity with the CNCF open-source community.• Enjoy working in a fast-paced and dynamic environment using the latest technologies
About UsHCL Cloud Native & AI Labs is the global Centre of Excellence guiding the application of advancedtechnologies and leading the way for clients and HCL employees worldwide.Our clients are the world’s largest enterprises, they engage with Labs for strategic advice,accelerated engineering, and industry thought leadership to guide their modernization andtransformation outcomes.We are the industry leader in Cloud-enabled transformation and work with the most advancedtechnologies, often leading the way for others. We sponsor industry bodies like the Cloud NativeComputing Foundation (CNCF) and contribute to successfully deploying emerging technologies.We deliver advanced engineering projects, enable industry collaboration, and work onenhancements to Kubernetes and other open-source projects driving change in the technologyindustry.