Lead Gen AI

Location: Hyderabad / Bangalore

Work Type: Hybrid

Gen AI JD:
-6 – 9 years of experience using analytical tools/languages like Python on large-scale data – Must have Semantic modelling & NER experience – Experience working with pre-trained models, awareness of state-of-art in embeddings and applicability for use cases – Must have strong experience in NLP/NLG/NLU applications using any popular Deep learning frameworks like PyTorch, Tensor Flow, BERT, Langchain and GPT (or similar models) Open CV.

• Must have exposure to Gen AI models (LLMs) like Falcon, Llama 2, GPT 3.5 & 4, Prompt Engineering
• Demonstrated ability to engage with client stakeholders at multiple levels and provide
  consultative solutions across different domains – Deep knowledge of techniques such as Linear Regression, gradient descent, Logistic
  Regression, Forecasting, Cluster analysis, Decision trees, Linear Optimization, Text Mining etc. – Strong understanding of integrating NLP models into business workflows. Prospect should have exposure to project initiation to business impact creation in at least one project.
• Experience in productionizing & retraining models
• Ability to guide and mentor teams of associates on solution development and approaches – Broad knowledge of fundamentals and state-of-the-art in NLP and machine learning – Coding skills in one or more programming languages such as Python, SQL – Expert / high level of understanding on language semantic concepts & data standardization – Proven track record of successful models and practical implementation – Hands-on experience with popular ML frameworks such as TensorFlow – Experience with application development practices at scale, from problem definition to deployment. – Familiarity with any Cloud services such as AWS, Sage Maker etc. is considered a plus – Develop and apply Statistical Modelling techniques (e.g Bayesian models and deep neural
  networks), optimization methods, and other ML techniques to different applications – Knowledge in Machine Learning techniques in entity resolution, common speech products or text search domain