MLOPS Engineer

Skills - Fine tune the LLM models, a strong understanding of transformer architecture and knowledge of RAG techniques, Python, Experience on MLOPS/LLMOPS (docker /container ). Have deploy the model in Production (GCP). Basic understanding of ML/Deep learning.NLP

Responsibilities:

• Help identify opportunities to solve complex challenges and deliver tangible business benefit through Analytics, Al/Machine Learning solutions and skillsets.
• Apply advanced Data Science methods, extensive prototyping and experimentation methodologles in the following disciplines: Data, Al: Machine Learning.
• Work closely and collaboratively with other functions within 8l & Analytics in order to assess the scalability of analytical opportunities and further development into production-level solutions.
• Running research experiments both in NLP & computer vision (for remote sensing based
  applications). 
• Should have good experience on Pyspark

Experience & Skills:

• Proficiency with python and the python ML tool kit along with DL frameworks
  Experience with working on end to end solutions and comfortable with cloud based ML-Ops pipelines
  Experience fine-tuning deep learning models including LLMs
  Experience with GPUs and understanding of balancing costs at both training and inference Comfortable in deploying end to end data science focused solutions with challenging data sets
• Proficiency/experience with ML deployment strategies, micro services and infrastructure
• ML-OPS experience with setting up CI/CD pipelines, feature engineering etis, designing feature stores and understanding mechanisms of deployment across various environments
• Experience in translating ML based outcomes to business-digestible insights