domain specific data.
Experience with RAG, Prompt Engineering concepts and fundamentals (Vector DBs).
Experience with containerization and orchestration technologies (Kubernetes, Docker).
In depth knowledge of machine learning, deep learning, and NLP.
Manage prioritization and technology work for building NLP, ML & AI solutions experience in experimenting and developing with LLM.
Strong understanding of NLP techniques and framework such as BERT,GPT or Transformer models.
Create and manage best practices for ML models integration, orchestration, and deployment, that will ensure secure including data versioning, ingress and model output egress, CI/CD pipelines for MLOps and LLMOps.
Solid understanding of Machine learning concept and algorithm including supervised and unsupervised learning, model evaluation and deployment strategies in production environment.
Follow AI best practices, ensuring fairness, transparency and accountability in AI model and system.

Skills Required / Qualification

At least 8-10 years of experience in deploying end to end data science focused solutions.
Should be strong technical background eg B.Tech /M.Tech from top tier institutes.
Expertise in training and fine tune LLMs using popular framework such as (TensorFlow, PyTorch or hugging face transformer) and deployment tools (eg Docker, Kubeflow)
Good exposure in Python.
Knowledge in SQL, Pandas or Pyspark.
Good to have understanding knowledge on GitHub, Confluence and JIRA
Cloud Platforms knowledge have to: Azure /GCP
Experience of senior stakeholder management and strong communication/presentation skills
Excellent verbal and written communication skills.
Present technical solutions, capabilities, considerations, and features in business terms.

We offer:

A work culture focused on innovation and building lasting value for our clients and employees
Ongoing learning opportunities to help you acquire new skills or deepen existing expertise
A flat, non-hierarchical structure that will enable you to work with senior partners and directly with clients
A diverse, inclusive, meritocratic culture
Enhanced and competitive family friendly benefits, including maternity / adoption / shared parental leave and paid leave for sickness, pregnancy loss, fertility treatment, menopause and bereavement

Machine Learning Engineer (MLops)