Strong experience with LLMs (LLaMA, DeepSeek, etc.) and understanding of RAG pipelines.
Hands on experience in Python, Linux, and Shell scripting
Experience with OpenCV, PyTorch, YOLO, or TensorFlow frameworks
Familiarity with LLM inference engines like Ollama, vLLM, llama.cpp
Solid knowledge of model conversion and deployment.
Experience working on AI Agents, LangChain, and retrieval-augmented generation (RAG)
Hands-on experience with Docker , Docker Compose, and integration into DevOps pipelines
Understanding of embedded platforms (Jetson, NXP, Qualcomm) and Yocto builds.
Experience in model optimization techniques (quantization, pruning, etc.)
Good grasp of CUDA kernels and GPU computing for acceleration
Excellent communication skills and the ability to collaborate effectively with cross-functional teams.
RESPONSIBILITIES:
Understanding functional requirements thoroughly and analyzing the client s needs in the context of the project
Envisioning the overall solution for defined functional and non-functional requirements, and being able to define technologies, patterns and frameworks to realize it
Determining and implementing design methodologies and tool sets
Enabling application development by coordinating requirements, schedules, and activities.
Being able to lead/support UAT and production roll outs
Creating, understanding and validating WBS and estimated effort for given module/task, and being able to justify it
Addressing issues promptly, responding positively to setbacks and challenges with a mindset of continuous improvement
Giving constructive feedback to the team members and setting clear expectations.
Bachelor s or master s degree in computer science, Information Technology, or a related field.
Job Classification
Industry: IT Services & ConsultingFunctional Area / Department: Data Science & AnalyticsRole Category: Data Science & Machine LearningRole: Data Science & Machine Learning - OtherEmployement Type: Full time