LLMOps Engineer - Data Science (8-10 yrs)

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.