Future Tech Jobs
Future Tech Jobs
You will play a key role in NVIDIA's JAX development, designing and implementing core components to optimize performance on NVIDIA products. Collaborate with AI researchers to build efficient, future-proof models and tools that bridge the gap between numerical computing and real-world applications.
You will play a key role in NVIDIA's JAX development, designing and implementing core components to optimize performance on NVIDIA products. Collaborate with AI researchers to build advanced models and tools that enhance the efficiency of AI systems, bridging the gap between cutting-edge research and real-world applications.
As a Machine Learning Engineer, you will collaborate with Data Scientists, Simulation Engineers, and customers to solve complex engineering and physics challenges. You will design, build, and test reliable, scalable ML data pipelines, manipulate 3D point cloud and mesh data, and ensure the successful deployment of AI models in real-world applications.
Develop and scale physical foundation models by bridging research and engineering, transforming prototypes into robust, optimised AI-driven simulation systems. Work across scientific computing, distributed training, and cloud infrastructure to deliver high-impact solutions for real-world engineering problems in collaboration with research teams, customers, and partners.
As a Software Engineering Manager, you will lead and develop a team of software engineers, establish engineering best practices, and drive the adoption of AI tooling and intelligent automation. You will work closely with product, architecture, and executive leadership to build innovative AI-driven platforms for the construction industry.
This role involves leading a small team of engineers in developing and maintaining a composable, API-driven CMS. Key responsibilities include defining engineering standards, managing AI-driven development, and fostering a collaborative engineering culture. The position offers opportunities for professional growth and a strong benefits package.
This role involves designing and conducting complex data creation tasks, including synthetic and model-based data generation, and coordinating human-in-the-loop data collections. You will work closely with cross-functional teams to ensure the AI systems are best in class, using Python and other tools for data analysis and creation.
This role involves building and evolving a scalable design system used across all Synthesia products, with a focus on making it AI-consumable. You'll design robust component APIs, ensure accessibility by default, and enhance developer experience through documentation and tooling. The position uniquely bridges human and AI-driven development, ensuring consistent, on-brand UIs are generated reliably whether by engineers or AI agents.
This role involves developing and deploying AI-powered features in a regulated healthcare environment, focusing on translating clinical and product requirements into secure, production-ready systems. The engineer will work across the full development lifecycle, integrating large language models and machine learning components into backend services while ensuring safety, reliability, and compliance. Collaboration with clinical and product teams is central to building measurable, patient-facing AI solutions.
This role involves designing and conducting complex data creation tasks, including synthetic and model-based data generation, and coordinating human-in-the-loop data collections. You will work closely with cross-functional teams to ensure the AI systems are best in class, using Python and other tools for data analysis and creation.
As a Staff ML Performance Engineer, you will focus on optimizing machine learning inference for edge devices and GPUs, working on large transformer-based models. You will collaborate with model developers, profile and optimize the full inference stack, and contribute to technical roadmaps and tooling.
This role involves building and optimizing production-scale machine learning systems for document classification and extraction, focusing on fraud detection in government-issued IDs. The engineer will work with LLMs and traditional ML models, design training and inference pipelines, and improve accuracy and performance across global document types. Collaboration with applied science, product, and operations teams is central to delivering secure and seamless customer onboarding solutions.
As a Platform Engineer, you will architect and maintain the infrastructure that enables the deployment of world-class AI solutions. You will work closely with the Applied AI team to build and refine data science, MLOps, and deployment tooling, ensuring high performance and seamless integration into diverse client environments.
This role involves building and optimizing production-scale machine learning systems for document classification and extraction, with a focus on fraud detection and identity verification. The engineer will work on LLM/ML pipelines, from training and evaluation to deployment and inference optimization, ensuring high accuracy and performance across global document types. Collaboration with cross-functional teams and mentorship of junior engineers are key aspects of the position.
This role involves designing and maintaining management services for Linux-based edge devices and PLC systems, automating deployments across global sites using Python, C#, and AWS IoT. The engineer will integrate cloud platforms with physical automation infrastructure, ensuring scalability, observability, and reliability of robotic retail solutions through CI/CD pipelines and cloud innovation.
