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Job Description
Job Responsibilities
● Architect and oversee the protocol's development, focusing on dynamic node orchestration, layer-wise model sharding, and secure, P2P network communication.
● Drive the end-to-end creation of AI applications, ensuring they are optimised for decentralised deployment and include use cases with autonomous agent workflows.
● Architect AI systems capable of running on decentralised networks, ensuring they balance speed, scalability, and resource usage.
● Design data pipelines and governance strategies for securely handling large-scale, decentralised datasets.
● Implement and refine strategies for swarm intelligence-based task distribution and resource allocation across nodes. Identify and incorporate trends in decentralised AI, such as federated learning and swarm intelligence, relevant to various industry applications.
● Lead cross-functional teams in delivering full-precision computing and building a secure, robust decentralised network.
● Represent the organisation's technical direction, serving as the face of the company at industry events and client meetings.
Requirements :
● Bachelor's/Master's/Ph.D. in Computer Science, AI, or related field.
● 12+ years of experience in AI/ML, with a track record of building distributed systems and AI solutions at scale.
● Strong proficiency in Python, Golang, and machine learning frameworks (e.g., TensorFlow, PyTorch).
● Expertise in decentralised architecture, P2P networking, and heterogeneous computing environments.
● Excellent leadership skills, with experience in cross-functional team management and strategic decision-making.
● Strong communication skills, adept at presenting complex technical solutions to diverse audiences.
Job ID: 107094055
Skills:
.NET, Microservices, Python, AWS, Apis, Sql, Devops, Gcp, Azure, AI Agents, pgvector, MCP Server, AI Governance, Pinecone, Security, OpenSearch, Vector Databases, CrewAI, LangChain, LLMs, Semantic Kernel, AutoGen, Enterprise AI Architecture, FAISS, RAG, LlamaIndex
Skills:
Microservices, Tensorflow, Pytorch, Docker, Azure, Kubernetes, Python, AWS, LangChain, enterprise search solutions, vector databases, LangGraph
Skills:
Machine Learning, Apis, Neural Networks, Dynamo Db, Python Programming, Solution Architecture, Prompt tuning, AWS Bedrock, Prompt engineering, Similarity search using vector databases, Embedding generation, Presales GTM, Llm, Agentic AI, Claude LLMs, Document ingestion
Skills:
API design, Distributed Systems, AI Platform architecture, Exposure to cloud ML tooling and MLOps practices, Reliability engineering, Building platform capabilities for AI ML or GenAI solutions
Skills:
Data Modeling, ELT, MLops, Etl, LLM ecosystems, Generative AI, Enterprise data platforms, Data engineering fundamentals, AI ML lifecycle, Cloud ecosystems, Enterprise architecture patterns, API integrations, AIOps