Senior Engineering Consultant-ai Science

Verizon Verizon · Telecom · Bangalore, India +2

Senior Engineering Consultant focused on designing, developing, and optimizing AI, SLM/LLM, and Agentic solutions. The role involves implementing algorithms, agentic design, performance tuning, defining APIs, and building toolsets. Requires hands-on experience in large-scale distributed systems for end-to-end AI training, LLM modeling (orchestration, fine-tuning, model serving), and deploying agentic solutions. Also involves prompt engineering, understanding compute systems for AI training, and research in generative AI.

What you'd actually do

  1. design, develop and optimize Artificial Intelligence, SLM/LLM and Agentic solutions to resolve diverse real-world problems
  2. implementing new algorithms, SLM/LLMs, Agentic design and build, performance/accuracy tuning and analysis, defining APIs, and analyzing functionality coverage to build larger, coherent toolsets and libraries
  3. Stay up-to-date with the latest advancements in generative AI, deep learning, and related fields
  4. Contribute to the research and development of novel generative models, exploring new algorithms and methodologies
  5. communicate complex model designs and outcomes in business terms to a non-technical audience

Skills

Required

  • cognitive analytics and AI Modeling
  • large-scale distributed systems
  • end-to-end AI training
  • SLM & LLM modeling
  • orchestration
  • fine tuning
  • model serving in production environment
  • agentic solutions at scale
  • GPU/CPU architecture
  • distributed computing
  • advance Prompt engineering and optimizations techniques
  • large-scale AI training
  • compute system concepts (latency/throughput bottlenecks, pipelining, multiprocessing etc)
  • performance analysis and tuning
  • Research and Development in generative AI, deep learning
  • novel generative models
  • new algorithms and methodologies
  • explain both the code and the underlying math used in algorithms/models
  • C++
  • Python
  • Java
  • debugging
  • performance analysis
  • TensorFlow
  • PyTorch

Nice to have

  • Generative AI techniques applied to Large Language Models
  • multimodal learning (Image, Video, Speech etc.)
  • mathematics
  • Statistics
  • algorithms
  • GCP/Azure/AWS
  • cloud technology
  • inference and deployment environments
  • Research, prototype, and develop effective tools and infrastructure pipelines
  • Publish innovative results on Github, scientific publications and patents
  • telecommunications industry data and use cases

What the JD emphasized

  • Must have hands-on experience in large-scale distributed systems capable of performing end-to-end AI. training and SLM & LLM modeling includes orchestration, fine tuning, model serving in production environment (batch/real time)
  • Proven track record of designing, developing and deploying agentic solutions at scale with measurable results mapped to business goals
  • Must have experience in Research and Development: Stay up-to-date with the latest advancements in generative AI, deep learning, and related fields

Other signals

  • designing, developing and deploying agentic solutions at scale
  • end-to-end AI. training and SLM & LLM modeling includes orchestration, fine tuning, model serving in production environment