Machine Learning Architect

2 weeks ago


kannur, India beBeeArtificial Full time

As a key member of our team, you will be responsible for designing and integrating cutting-edge machine learning models and algorithms.Job RequirementsYour role will involve collaborating closely with cross-functional teams to recognize and establish project objectives, overseeing data infrastructure maintenance, and ensuring streamlined and scalable data operations.Develop, validate, and implement machine learning models and algorithms.Collaborate with data scientists and other stakeholders to understand and define project goals.Maintain data infrastructure and ensure scalability and efficiency of data-related operations.Stay up-to-date with advancements in AI and propose their integration for operational enhancement.Effectively communicate complex data findings clearly and understandably to non-technical stakeholders.Adhere to data privacy and security guidelines.Participate in the entire AI project lifecycle, from concept to deployment and maintenance.Required Skills:Strong grasp of computer architecture, data structures, system software, and machine learning fundamentals.Experience with mapping NLP models (BERT and GPT) to accelerators and awareness of trade-offs across memory, bandwidth, and compute.Experience with Vector databases like Qdrant, ChromaDB, Pinecone, PGVector or similar.Experience with Large language Models like GPT 3.5, GPT 4, Llama, Gemini, Mistral etc.Experience in design, build, and optimization of agentic AI workflows that enable autonomous reasoning, decision-making, and tool interaction using frameworks like LangChain, LangGraph, CrewAI, etc.Experience in implementation and fine-tuning Generative AI solutions (e.g., LLMs, multimodal models) for various business use cases.Proficiency in Python development in a Linux environment and using standard development tools.Experience with deep learning frameworks (such as PyTorch, Tensorflow, Keras, Spark).Working knowledge of Artificial Neural Networks (ANNs), Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), and Generative Adversarial Networks (GANs).Experience in training, tuning, and deploying ML models for Computer Vision (e.g., ResNet), and/or Recommendation Systems (e.g., DLRM).Experience deploying ML workloads on distributed systems.Self-motivated team player with a strong sense of ownership and leadership.Strong verbal, written, and organizational skills for effective communication and documentation.Research background with a publication record.Work experience at a cloud provider or AI compute/sub-system company.Knowledge of cloud computing platforms and services, such as AWS, Azure, or Google Cloud.Experience with information security and secure development best practices.



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