Dist Engr-ai Science

Verizon Verizon · Telecom · Bangalore, India +2

Distinguished Engineer role focused on architecting and designing AI/ML agentic systems, including data pipelines, model training, deployment, and optimization. Requires extensive experience in large-scale AI/ML systems, NLP, LLM fine-tuning and evaluation, and deploying agentic solutions. The role involves leading a team, mentoring, and championing AI best practices.

What you'd actually do

  1. Design, develop, and deploy end-to-end AI/ML solutions, including data pipelines, model training, deployment, monitoring, and optimization.
  2. Develop technical high level and low level architecture for generative and agentic systems
  3. Lead and mentor a high performing team of data scientists and AI/ML engineers, fostering a culture of collaboration and innovation.
  4. Stay abreast of the latest advancements and trends in Generative/Agentic AI, continuously evaluating and integrating emerging technologies.
  5. Collaborate closely with cross-functional teams, including product, engineering, and business stakeholders, to translate business requirements into innovative AI/ML solutions.

Skills

Required

  • Master’s or Ph.D. degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field
  • 12+ years of experience in architecting, designing, and implementing large-scale AI/ML systems in a production environment
  • implementation of large-scale NLP Projects and Fine tuning & Evaluation of LLMs for downstream tasks such as text generation, Classification, summarization, question answering, entity extraction etc.
  • designing, developing and deploying agentic solutions at scale with measurable results mapped to business goals
  • Machine Learning, Deep Learning model development & deployment from scratch in Python
  • NLP frameworks and libraries like NLTK, Spacy, Transformers, Pytorch, Tensorflow, hugging face api’s
  • supervised and unsupervised ML algorithms
  • data preprocessing techniques
  • Deep Learning i.e Convolutional Neural Nets (CNN), Recursive Neural Nets (RNN) & Long Short Term Memory (LSTM), Generative Adversarial Networks (GAN), Deep Reinforcement Learning
  • RESTful, JSON API services
  • Word embeddings, TF-IDF, Tokenization, N-Grams, Stemmers, lemmatization, Part of speech tagging, entity resolution, ontology, lexicology, phonetics, intents, entities, and context
  • analyzing Live Chat/call conversation with agents
  • Python, Sql, PySpark, Scala and/or other languages and tools
  • validation framework for generative model output
  • GPU/CPU architecture and distributed computing and general infra needs to scale Gen AI models
  • MLOps tools and best practices

Nice to have

  • Contributions to open-source AI/ML projects
  • Familiarity with telecommunications industry data and use cases

What the JD emphasized

  • at least 12+ years of experience in architecting, designing, and implementing large-scale AI/ML systems in a production environment
  • implementation of large-scale NLP Projects and Fine tuning & Evaluation of LLMs
  • Proven track record of designing, developing and deploying agentic solutions at scale

Other signals

  • architecting and designing large-scale AI/ML systems in a production environment
  • implementation of large-scale NLP Projects and Fine tuning & Evaluation of LLMs
  • designing, developing and deploying agentic solutions at scale