2 of 2 Data Ingestion Jobs in Hounslow

join with: Mission: Build and enhance a platform that supports the collection and analysis of intelligence related to cryptocurrency crime. The role involves developing tools and systems to streamline data ingestion from various sources and integrate it into a proprietary graph database. Key Responsibilities: Design and develop software tools for intelligence collection and analysis. Create systems to analyze … practices. Contribute to the team’s technical strategy and decision-making. Ideal Candidate: Passionate about cryptocurrencies and blockchain technology. Experience integrating systems to improve operational efficiency. Collaborative, communicative, and data-driven in decision-making. Required Experience: 5+ years of commercial software engineering experience. Proficiency with AWS, Kubernetes, Postgres, and Terraform. Bonus Skills: Background in intelligence collection or big data. More ❯

Social network you want to login/join with: Nscale is taking on the hyperscalers by building a vertically integrated GenAI cloud platform. We own the data centres, software, and applications that power today's AI stack using sustainable technology solutions. We thrive on a culture of relentless innovation, ownership, and accountability, where every team member takes pride in … inference of generative AI models. Design and implement advanced methodologies like LoRA, prefix-tuning, and adapter-based approaches for fine-tuning AI models. Develop robust, fault-tolerant systems for data ingestion, processing, and model customisation. Optimise GPU utilisation and system performance using frameworks like DeepSpeed, Triton Inference Server, TensorRT, and custom CUDA/Rocm kernels. Conduct performance testing … production environments. Proficiency in Python and PyTorch, with a strong understanding of transformer architectures, LLMs, and multimodal generative models. Expertise in distributed training frameworks like DeepSpeed or Fully Sharded Data Parallel (FSDP). Experience with GPU programming and optimisation e.g CUDA, TensorRT, or ROCm. Knowledge of fine-tuning methods, such as LoRA, prefix-tuning, and adapter-based techniques, and More ❯