Role Description Validate the ML stack that turns accelerator hardware into trusted AI performance. This role sits where modern ML models meet Graphcore’s software and hardware stack. You will test, benchmark and validate complex systems before they reach customers. - Your work will expose regressions, correctness issues and performance limits across frameworks, models and execution environments. - You will help teams understand what is working, what is breaking and why. - You will run open source models, build automated benchmarking pipelines and create targeted tests for low level ML behaviour, including: - Numerical precision - Quantisation - Attention mechanisms - Distributed execution - Model subgraphs - This is a role for someone who wants to stay close to how AI systems really work. You will not design new models, but you will make them run reliably on ambitious infrastructure. Qualifications - Strong experience in Machine Learning or ML-adjacent software engineering roles. - A solid grasp of neural networks, training, inference, numerical precision and performance trade-offs. - Hands-on experience with PyTorch, TensorFlow, JAX, Triton or similar ML frameworks and tools. - Strong Python skills for automation, experimentation, benchmarking and reporting. - Experience designing, running and analysing ML benchmarks or model experiments. - Confident debugging skills in Linux, with curiosity about model behaviour and system performance. Benefits - Unlimited annual leave - Up to 5% matched pension - Phantom equity – share in Graphcore’s success - True flexibility in how and where you work - Office spaces designed for collaboration - Free food and an on-site barista - Health cash plan - Income protection - Life assurance - Along with other benefits you can choose from (private medical insurance, dental plan etc)

Role Description Validate the ML stack that turns accelerator hardware into trusted AI performance. This role sits where modern ML models meet Graphcore’s software and hardware stack. You will test, benchmark and validate complex systems before they reach customers. - Your work will expose regressions, correctness issues and performance limits across frameworks, models and execution environments. - You will help teams understand what is working, what is breaking and why. - You will run open source models, build automated benchmarking pipelines and create targeted tests for low level ML behaviour, including: - Numerical precision - Quantisation - Attention mechanisms - Distributed execution - Model subgraphs - This is a role for someone who wants to stay close to how AI systems really work. You will not design new models, but you will make them run reliably on ambitious infrastructure. Qualifications - Strong experience in Machine Learning or ML-adjacent software engineering roles. - A solid grasp of neural networks, training, inference, numerical precision and performance trade-offs. - Hands-on experience with PyTorch, TensorFlow, JAX, Triton or similar ML frameworks and tools. - Strong Python skills for automation, experimentation, benchmarking and reporting. - Experience designing, running and analysing ML benchmarks or model experiments. - Confident debugging skills in Linux, with curiosity about model behaviour and system performance. Benefits - Unlimited annual leave - Up to 5% matched pension - Phantom equity – share in Graphcore’s success - True flexibility in how and where you work - Office spaces designed for collaboration - Free food and an on-site barista - Health cash plan - Income protection - Life assurance - Along with other benefits you can choose from (private medical insurance, dental plan etc)

Role Description Worley is a global company of energy, chemicals and resources experts headquartered in Australia. We partner with our customers to deliver projects and create value across the life of their assets. We specialize in consulting, engineering, procurement and construction across the project lifecycle, with services extending through to operations and decommissioning. Leveraging extensive experience and AI-enabled delivery, we support customers in navigating complexity as they meet today's needs and transition to more sustainable solutions. Qualifications - Cursando Ensino superior em Geologia, Engenharia Ambiental, Gestão Ambiental, Ciências Ambientais entre outras. - Conhecimento dos tópicos relacionados ao processo caracterização ambiental e às técnicas de remediação. - Autonomia, capacidade trabalho em equipe e habilidades de comunicação oral e escrita. - Experiência de estudos em campo (nível universitário). - Conhecimentos acadêmico com bases de dados, software estatísticas, GIS, CAD, ou Power BI desejável. - Motivação e habilidade de trabalho em equipe. - Disciplina e condições de estagiar remoto (home office). - Dominio de pacote Office. Benefits - We want our people to be energized and empowered to drive sustainable impact. - Focus on a values-inspired culture that unlocks brilliance through belonging, connection and innovation. - Building a diverse, inclusive and respectful workplace. - Creating a space where everyone feels they belong, can be themselves, and are heard. - Reskilling our people and supporting the transition of our workforce to become experts in today's low carbon energy infrastructure and technology. - Opportunities to broaden horizons and explore diverse opportunities. - Be part of delivering sustainable change.

Role Description - Execute test cases (manual and automated) to validate functionality, usability, and performance of software applications. - Assist in the creation and maintenance of test plans, test cases, and test data. - Perform functional, regression, and integration testing under guidance from senior team members. - Identify, log, and track defects, ensuring clear documentation and timely follow-up. - Support API and backend testing using tools such as Postman or similar platforms. - Collaborate with developers, product managers, and QA team members to understand requirements and ensure quality deliverables. - Participate in Agile ceremonies such as sprint planning, daily stand-ups, and retrospectives. - Contribute to test automation efforts by writing and maintaining basic test scripts. - Execute test suites within CI/CD pipelines and report results. - Maintain accurate documentation of test execution results and quality metrics. - Learn and apply AI-assisted tools to improve testing efficiency and documentation. - Continuously build knowledge of QA methodologies, tools, and best practices. Qualifications - 1–3 years of experience in software testing or quality assurance (internships included). - Basic understanding of software testing concepts, types, and methodologies. - Familiarity with manual testing of web applications or APIs. - Exposure to at least one programming or scripting language (e.g., Java, Python, JavaScript) is a plus. - Familiarity with test management and defect tracking tools (e.g., Jira, TestRail, or similar). - Understanding of the Software Development Lifecycle (SDLC) and Agile methodologies. - Strong attention to detail and willingness to learn. - Good communication and collaboration skills. Requirements - Exposure to test automation tools such as Selenium, Cypress, or Playwright. - Basic knowledge of API testing tools like Postman. - Familiarity with CI/CD concepts and tools (e.g., Jenkins, GitHub Actions). - Exposure to cloud-based applications or environments (AWS, Azure, or similar). - Interest in learning performance or security testing practices. Benefits - This role encourages the use of modern tools, including AI, to build strong quality engineering foundations. - The ideal candidate is curious about how AI can assist with test creation, debugging, and documentation. - Approaches problems with a learning mindset: “How can I improve quality and efficiency using tools and automation?” - Is open to experimentation and continuous learning. - Focuses on delivering reliable, high-quality software while growing technical skills.