Ai Ml Engineer

Role Overview:

AI/ML Engineer

Mandatory Skills:

• AI/ML Expertise

• Strong background in

  Computer Vision (CV)

  ,

  Natural Language Processing (NLP)

  , and

  Speech models

• Experience with

  multimodal transformer architectures

• High-Performance Computing

• GPU optimization

  for large-scale deep learning workloads

• Distributed training

  using

  DeepSpeed

  and

  Horovod

• Real-Time Systems

• Proven experience in

  real-time / near-real-time video processing

• MLOps & Deployment

• Hands-on with

  MLflow

  ,

  Ray

  ,

  Airflow

• Model serving with

  KServe

  and

  Triton Inference Server

• Retrieval-Augmented Generation (RAG) & LLM Tooling

• Experience with

  Vector Databases

  (e.g., FAISS, Milvus, Pinecone)
• Familiarity with

  LangChain

  for building RAG pipelines

Good-to-Have Skills

• Experience with

  broadcast/OTT platforms

  ,

  MAM systems

  , and

  DAM workflows

• Exposure to

  generative imaging

  (e.g.,

  Stable Diffusion

  ) or

  video generation

Responsibilities

• Design, train, and optimize

  multimodal AI models

  for CV, NLP, and speech tasks
• Implement

  distributed training pipelines

  across GPUs/nodes for large-scale models
• Develop

  real-time video processing solutions

  for production environments
• Deploy models using

  KServe/Triton

  and integrate with scalable MLOps workflows
• Build

  RAG-based applications

  leveraging vector databases and LangChain
• Collaborate with cross-functional teams to deliver

  AI-driven products

  at scale

Qualifications

• Bachelor’s/Master’s/PhD in

  Computer Science, AI/ML, or related field

• 4–8 years of experience in

  AI/ML engineering

  with focus on multimodal systems
• Strong programming skills in

  Python

  and deep learning frameworks (

  PyTorch, TensorFlow

  )
• Solid understanding of

  distributed systems

  and

  GPU computing