Mine and analyse data from data sources to develop new products offering or drive optimisation and improvement of product development, marketing techniques and business strategies.
Build AI-powered features into business applications — such as integrating LLM APIs, embedding AI assistants, or adding intelligent automation — to enhance existing Java, .NET Core, and TypeScript applications.
Provide expertise in deploying AI, machine learning, generative AI, and automation solutions, ensuring they deliver measurable business outcomes and operational improvements.
Mine and analyse data from data sources to develop new products offering or drive optimisation and improvement of product development, marketing techniques and business strategies.
This is a start up-style role with broad ownership across AI development, data collection, robot integration, testing, failure analysis, and continuous performance improvement. The ideal candidate is comfortable working across disciplines and taking ideas from early experimentation through to real-robot deployment.
Mine and analyse data from data sources to develop new products offering or drive optimisation and improvement of product development, marketing techniques and business strategies.
· Take technical ownership of telecom engineering packages through feasibility, concept, FEED, and detailed design, and approve system architecture and key design decisions.
Manage the complete sales cycle from lead generation, customer discovery, solution presentation, proposal preparation, negotiation, and contract closure.
We are looking for a hands-on Embodied AI Engineer with experience in robot learning to develop, fine-tune, deploy, and validate intelligent behaviors on physical humanoid robots.
Lead consultative discovery to understand customers' AI applications, model stack, workloads, buying process, and success criteria. Develop business cases that connect model quality, latency, throughput, and total cost of ownership to customer outcomes
Lead consultative discovery to understand customers' AI applications, model stack, workloads, buying process, and success criteria. Develop business cases that connect model quality, latency, throughput, and total cost of ownership to customer outcomes