LLM Ops 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.