Our Client Currently looking for Data Scientist II – NLP/Machine Learning

Responsibilities :

– Develop Computer Vision, AI, and ML techniques to detect and classify vehicular and other road objects, track and re-identify them, and generate KPIs for traffic analytics to be deployed at scale across approximately 6000 cameras.

– Build large-scale vision applications requiring optimizations such as pruning, quantization, architecture tuning, and deployment optimization for like models in terms of VRAM usage, latency, throughput, and model size.

– Deploy models in high-performance inference systems such as Triton Inference Server and optimize inference pipelines potentially at CUDA/TensorRT level.

– Work on end-to-end MLOps including experiment tracking, architecture search, model tuning, reproducibility, inference deployment, distributed training, and scalable AI infrastructure.

– Understand, reproduce, and innovate on top of latest research papers related to Computer Vision, Deep Learning, multimodal AI, and semantic AI systems.

– Develop NLP and LLM-powered systems for applications including semantic search, question-answering systems, summarization, knowledge extraction, and document understanding.

– Design and implement retrieval systems using techniques such as RAG (Retrieval-Augmented Generation), Knowledge Graph Augmented Generation (KAG), vector databases, embeddings, and semantic reasoning pipelines.

– Build and maintain Knowledge Graphs and semantic data models using technologies such as RDF/OWL, SPARQL, Graph Databases, and healthcare interoperability standards.

– Develop AI pipelines for extracting structured information from unstructured and multimodal data sources including PDFs, scanned documents, healthcare claims, clinical notes, reports, and video feeds.

– Work on multimodal AI systems integrating Computer Vision, NLP, Knowledge Graphs, geospatial systems, and distributed analytics infrastructure.

– Contribute to scalable distributed AI systems involving technologies such as Ray, Dask, Kubernetes, distributed inference, and large-scale model serving.

– Collaborate closely with interdisciplinary researchers, engineers, domain experts, and public-sector stakeholders across mobility, healthcare, and urban systems domains.

Are you interested in this position?

Apply by clicking on the “Apply Now” button below!

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