Lead Data Engineer(GenAI)

1 month ago


Bengaluru, India Wipro Full time

Exciting Opportunity for Generative AI Leader at Wipro.

Position- Lead/Architect Data Engineer

Experience- 6 Years to 12 Years

Location- Kolkata, Pune, Bengaluru

Candidate Requirement (JD)

  • Minimum 6+ years of experience with designing and implementing AI/ML model, out of which minimum 2+ years on implementing GenAI based solutions.
  • Strong implementation expertise around foundation models like computer vision models (ResNet, EfficientNet, YOLO) and Generative Model Transformers (GANs, VAEs) to augment the intelligence of low latency predictive algorithms.
  • Experience in development and deployment of Models in battery powered Compute Devices having GPUs/TPUs/NPUs accelerators for offline inferencing.
  • Experience with deploying and fine tuning Large Multi-modal models with capability of audio synthesis, generative image and video.
  • Conversant with Quantization, Speculative Decoding, Kernel Fusion, CoT, RAG, PeFT.
  • Conversant with model evaluation techniques and benchmarks.
  • Conversant with design, develop, and optimize data pipelines for ingesting, processing, and transforming large-scale data from various sources (structured and unstructured).
  • Create and maintain data models that align with ML requirements.
  • Deploy ML models (Computer Vision, NLP) into production systems and operationalize MLOps.
  • Knowledge of ML frameworks (TensorFlow, PyTorch, OpenCV) and familiarity with deep learning concepts is a must.
  • Experience with cloud platforms (e.g., AWS, GCP, Azure) and containerization (Docker, Kubernetes).
  • Strong proficiency in Python, SQL, and ETL tools (e.g., Apache Spark, Airflow).

Mandatory Skill: Device side GenAI implementation. Experience with quantizing inference model (LLM/LMM) and deploying on devices with limited compute and memory. Preferably worked on deploying and running ML/LMM models on NVIDIA, QUALCOMM chipsets, etc.

Good to have skill : Conversant with Quantization, Speculative Decoding, Kernel Fusion.

GGUF, LoRA, PeFT, Knowledge Distillation.


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