Design and build data pipelines, APIs, and backend services using Python and AWS, with a focus on processing complex datasets and deploying machine learning models into production. Work within a cloud-native environment to transform raw data into actionable insights using modern software engineering practices and data science techniques.
This role involves designing and building scalable, reliable data infrastructure to support advanced analytics and machine learning. You will work closely with data science and analytics teams to architect robust data pipelines and services, ensuring data quality and reliability in a cloud environment.
Design and maintain a scalable, secure data platform on Azure and Snowflake, using infrastructure-as-code (Terraform) and CI/CD pipelines (Azure DevOps, GitHub Actions). Implement observability, security, and automation practices while mentoring junior engineers and collaborating with data science and business teams. Focus on enabling advanced analytics in a healthcare and insurance context.
This role involves working closely with sales teams and customers to demonstrate the technical capabilities of the Databricks Data Intelligence Platform, particularly in data and AI use cases. The engineer will lead hands-on evaluations, develop custom demos and reference architectures, and act as a trusted advisor on data solutions across industries like media, financial services, and retail. The position requires strong technical communication skills, coding ability in Python, Java, or Scala, and experience in data engineering or machine learning environments.
Design and demonstrate GPU-accelerated solutions leveraging NVIDIA and GCP technologies for enterprise and developer audiences. Support partners and customers in optimizing GenAI and machine learning workloads across training and inference pipelines. Collaborate with engineering and product teams to integrate NVIDIA platforms into hyperscaler environments, with a focus on real-world performance and scalability.
This role involves designing and demonstrating GPU-accelerated solutions on hyperscaler platforms, with a primary focus on Google Cloud (GCP), to support enterprise adoption of NVIDIA's Generative AI and machine learning technologies. The Solutions Architect will collaborate closely with developers, data scientists, and technical leaders to optimize training and inference pipelines, deliver proof-of-concepts, and integrate NVIDIA software and hardware into cloud-based AI workflows. A strong technical background in AI/ML systems and cloud infrastructure, along with the ability to translate complex challenges into scalable solutions, is central to the position.
This role involves working on short to medium-term customer engagements to solve big data challenges using the Databricks platform. You'll design and implement data engineering and data science solutions, integrate with client systems, provide technical training, and act as an escalation point for complex issues. The position emphasizes hands-on implementation, customer collaboration, and feedback to product teams to improve platform capabilities.
Senior Python Software EngineerLocation: London, UKWorking Environment: HybridThe company is a leading financial data and analytics company who are looking to hire a Senior Software Engineer with experience of working on the development of SaaS applications.As a Senior Software Engineer,...
Design and build scalable AI platforms and data pipelines, productionising machine learning and NLP models into cloud-native services. Collaborate with data scientists and engineers to deliver intelligent, real-world products using modern MLOps practices. Mentor junior engineers and influence technical standards in a collaborative, innovation-driven environment.
Conduct research in reinforcement learning and guided search for agentic AI systems, focusing on scalable training methods, web-scale data mining, and efficient model distillation. Work closely with engineering teams to translate research into production AI capabilities, using JAX and distributed training frameworks. Publish findings and contribute to cutting-edge advancements in reasoning models and agent-based systems.
This role involves shaping the technical strategy and go-to-market approach for a cloud AI platform tailored to retail and commerce. You'll work closely with enterprise customers' CTOs, translate real-world demands into product requirements, and architect solutions for agentic commerce, recommendation systems, and supply chain optimization. The position bridges deep technical expertise with executive engagement to define a new category of AI infrastructure.
This role involves hands-on engineering and architectural leadership for an enterprise Azure Databricks platform, focusing on serverless optimisation, FinOps implementation, and migration from POSIT/RStudio. The engineer will design and enhance data pipelines, enforce cost controls through tagging and budgeting, and enable secure, scalable integration patterns. Key responsibilities include performance tuning, workload placement, and supporting data science workloads in a hybrid environment.
This role involves building and maintaining scalable data pipelines for AI/ML applications, with a focus on data infrastructure and quality. You'll work closely with data science and product engineering teams to enable robust data tracking, ingestion, and monitoring using modern cloud technologies. The position emphasizes ownership of technical design and cross-team collaboration in a global SaaS environment.
Please note this is a remote working role from the UK**Hexwired has partnered with a company who are an AI Start up and are already excelling in their field. They are looking for a Full Stack Engineer who will build...
Act as a trusted technical advisor to enterprise clients, demonstrating Snowflake's platform through tailored presentations and proof-of-concept engagements across the sales cycle. Collaborate with sales, product, and engineering teams to shape solutions for complex data challenges in cloud analytics and AI, while building customer technical champions and influencing product direction. Stay ahead of industry trends and competitive landscapes, particularly in financial services, to position Snowflake as a strategic data platform.
