LLMOps Engineer - Data Science

Mandatory Skills & Experience : - Expertise in designing and optimizing machine-learning operations, with a preference for LLM Ops. - 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 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, working 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, and 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. Desired Skills & Experience : - Bachelor level technical degree or equivalent experience; Computer Science, Data Science, or Engineering background preferred; Master's Degree desired. - Experience in LLM Ops or related areas, such as DevOps, data engineering, or ML infrastructure. - Hands-on experience in deploying and managing machine learning and large language model pipelines in cloud platforms (i.e., AWS, Azure) for ML workloads. - Familiar with data science, machine learning, deep learning, and natural language processing concepts, tools, and libraries such as Python, TensorFlow, PyTorch, NLTK etc. - Experience in using retrieval augmented generation and prompt engineering techniques to improve the model's quality and diversity to improve operations efficiency. - Proven experience in developing and fine-tuning Language Models (LLMs). - Stay up-to-date with the latest advancements in Generative AI, conduct research, and explore innovative techniques to improve model quality and efficiency. - The perfect candidate will already be working within a System Integrator, Consulting or Enterprise 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. (ref:hirist.tech)

Location: noida, IN

Posted Date: 4/19/2025