Future Tech Jobs
Future Tech Jobs
You will architect and optimize high-performance AI inference systems, focusing on GPU kernel optimization, benchmarking, and large-scale deployment across multi-cloud environments. This role involves deep collaboration with cross-functional teams to push the boundaries of accelerated computing for AI.
You will architect and optimize high-performance AI inference systems, focusing on GPU kernel optimization, compiler development, and benchmarking. Collaboration with cross-functional teams and publishing original research are key aspects of this role.
This role involves working in a fast-paced, interdisciplinary team to build a cutting-edge ML-based software platform for drug discovery. Responsibilities include data engineering, service-oriented architecture, and collaboration with scientists and ML researchers to accelerate scientific breakthroughs using AI.
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 Software Engineer, you will play a crucial role in building and operating the inference platform, connecting deep expertise in distributed systems programming with hands-on knowledge of Kubernetes-based platforms. You will support the platform in production, ensuring high-quality, user-focused features and maintaining platform stability, reliability, and scalability.
This role involves developing high-fidelity pre-silicon models of AI acceleration hardware using C++ and SystemC to enable architectural exploration, performance analysis, and early software development. The engineer will work in close collaboration with hardware, software, and machine learning teams within a co-design framework, directly influencing the design and performance of Fractile's next-generation AI accelerators.
You'll develop high-fidelity pre-silicon models of AI acceleration hardware using C++ and SystemC, enabling architectural exploration, performance analysis, and early software development. Working in close collaboration with hardware, software, and ML teams, your models will directly shape Fractile's hardware design and performance characteristics before silicon exists.
This role involves building and maintaining a Snowflake-based data platform, designing ELT/ETL pipelines using dbt and Python, and ensuring data quality through governance and security standards. The engineer will collaborate with analysts and business teams to deliver clean, structured data for reporting and support future AI/ML initiatives. Key responsibilities include optimising Snowflake performance, implementing monitoring and cost controls, and contributing to data engineering best practices.
This role involves designing and building production-ready AI features using large language models, machine learning, and retrieval-augmented generation (RAG) to enhance digital products. The engineer will bridge AI concepts with real-world applications, focusing on automation, product intelligence, and responsible AI practices. Collaboration with product teams and engineers is key to delivering secure, scalable solutions grounded in business needs.
Design and build enterprise-scale generative AI platforms, including chatbots, RAG systems, and agentic workflows, integrated into financial data products. Develop production-ready AI infrastructure using Python, LangChain, and cloud technologies on AWS or Azure. Collaborate across engineering and product teams to deploy scalable, full-stack AI solutions that deliver real-time business impact.
As an Applied AI Engineer, you will work directly with enterprise clients to build advanced AI solutions, ranging from cybersecurity to journalism and genomics. Your role involves gathering business requirements, translating them into technical solutions, and optimizing AI models to meet client needs. You will collaborate with cross-functional teams, write production code, and leverage the Scale Generative Platform (SGP) to develop cutting-edge AI agents.
This role involves designing, building, and maintaining robust cloud platforms and CI/CD pipelines on GCP. You will collaborate with cross-functional teams to deliver scalable, reliable solutions, provide technical leadership, and stay current with emerging technologies.
Design and build data ingestion pipelines using Apache Spark and Azure Databricks, model data using Lakehouse architecture, and create dashboards and semantic layers for business stakeholders. Collaborate with data scientists to productionise machine learning pipelines within an Agile environment, ensuring high data quality from source to target systems.
In this role, you will design, build, and scale backend systems that power enterprise GenAI products, focusing on reliability, performance, and deployment across both Scale’s and customers’ infrastructure. You will develop core services and APIs, architect scalable distributed systems, and optimize backend performance for latency, throughput, and cost.
The Senior AI Engineer will design and develop production-grade AI systems, focusing on RAG pipelines, generative AI workflows, and LLM optimization. Key responsibilities include building scalable solutions, implementing retrieval strategies, and mentoring junior engineers within a growing AI team.
