LC
AI/ML Inference SDK Lead for a Wireless Tech org @Chennai/Hyderabad– 30-80L
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Chennai · On-site Full-time Lead Today
About the role
Note
- The client is hiring for multiple levels starting from 6-12+yrs of experience.
Role
- The role needs a multiple highly skilled Machine Learning & Data Science Engineers who can independently drive end‑to‑end development of scalable data pipelines, ML/NLP models, and production‑grade Python systems.
- He/she should have strong technical depth across Machine Learning, NLP, Data Engineering, and Python backend development. The roles require deep expertise in C++ and embedded systems to commercialize scalable inference solutions.
- He/she would be driving high‑performance inference for large‑scale GenAI models.
- Optimize AI/ML stacks across CPU, GPU, and NPU hardware accelerators.
- Apply best practices in deploying large C/C++ software stacks.
- Stay ahead of GenAI advancements (LLMs, Transformers, edge deployment).
Requirements
AsK:
- 6-12+yrs of total experience with a Bachelor’s/master’s in computer science or related field from a Tier 1 institute
- 6+years of software development experience with strong proficiency in C/C++, OS concepts, and design patterns.
- Experience with AI hardware accelerators (CPU, GPU, NPU).
- Hands‑on work with Generative AI models (LLMs, embeddings, vector databases).
- Strong Python skills for integration and testing.
- Excellent debugging, analytical, and communication skills.
- Familiarity with CUDA/OpenCL and parallel computing.
Requirements
- 6+ years of software development experience with strong proficiency in C/C++, OS concepts, and design patterns.
- Experience with AI hardware accelerators (CPU, GPU, NPU).
- Hands-on work with Generative AI models (LLMs, embeddings, vector databases).
- Strong Python skills for integration and testing.
- Excellent debugging, analytical, and communication skills.
- Familiarity with CUDA/OpenCL and parallel computing.
Responsibilities
- Drive end-to-end development of scalable data pipelines, ML/NLP models, and production-grade Python systems.
- Drive high-performance inference for large-scale GenAI models.
- Optimize AI/ML stacks across CPU, GPU, and NPU hardware accelerators.
- Apply best practices in deploying large C/C++ software stacks.
- Stay ahead of GenAI advancements (LLMs, Transformers, edge deployment).
Skills
C++CUDAData EngineeringGenerative AIGPULLMsMachine LearningNPUNLPNumpyOpenCLOS conceptsPythonTransformersVector databases
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