• Explore and apply advanced machine learning techniques, including large language models (LLMs), deep learning, and graph neural networks, to solve complex challenges across the organization. • Collaborate with management and stakeholders to define strategic roadmaps and translate them into actionable quarterly plans. • Design and deliver scalable, secure systems using state-of-the-art AI/ML technologies and industry best practices. • Troubleshoot and resolve complex technical issues to improve system reliability, scalability, and operational efficiency. • Ensure the security, scalability, and architectural integrity of feature designs through reviews across teams. • Mentor other data professionals (including MLEs) within the organization.

• Lead ML model creation, support foundational standardization • Create machine learning model architecture, parameters, and related technical specifications to accurately classify education finance data to a common reporting structure. • Guide staff in the sourcing, preparation of training data for machine learning models that map local accounting codes to standardized national categories. • Develop and implement model features derived from raw financial records, metadata, and related datasets. • Lead model iteration, evaluation, and improvement process with technical team members in support. • Provide analytical support in translation process. • Support processes and statistical rules for transforming current federal data into a nationally comparable, complete, and actionable dataset by identifying opportunities for efficiency and accuracy improvements. • Address reporting discrepancies—such as varying state treatments of teacher pensions and debt—to create a standardized foundational dataset.

• Join a leading AI lab's cutting-edge Generative AI team and play a key role in developing next-generation large language models. • Contribute to AI model training and evaluation initiatives by designing, solving, and reviewing advanced machine learning infrastructure and systems challenges. • Your expertise will help improve the quality of training data used to develop frontier AI systems. • Partner with research and engineering teams to identify and address knowledge gaps in MLOps, machine learning infrastructure, and model training systems. • Design challenging, real-world tasks focused on distributed training, ML frameworks, model optimization, and infrastructure engineering. • Develop accurate, well-structured solutions to complex MLOps and ML systems problems. • Evaluate technical tasks and solutions, providing detailed and actionable feedback. • Create evaluation frameworks and scoring rubrics for training pipeline architecture, distributed systems reasoning, performance optimization, and kernel-level programming. • Contribute domain expertise to improve AI model capabilities in machine learning engineering topics. • Collaborate with other subject matter experts to ensure consistency, quality, and technical accuracy across datasets and evaluations.

Role Description The Applied Machine Learning Engineer will be a member of Terra Quantum's AI Applied Research team. This team builds and delivers end-to-end machine learning solutions for industrial clients across various domains. - Own the classical machine learning craftsmanship from data exploration to client delivery. - Incorporate a quantum layer as one architectural component of an otherwise classical pipeline. - Apply classical ML methods to make hybrid solutions perform reliably on real industrial data. - Drive excellence within the team by demonstrating commitment and passion for the mission. Responsibilities - Building and delivering industry machine learning solutions. - Designing end-to-end ML pipelines for client problems in: - Time series - Routing and planning - GenAI - Natural language processing - Computer vision - Predictive modelling - Choosing the right classical method based on data characteristics. - Treating the quantum layer as a constrained component of the model. - Performing classical machine learning craftsmanship in service of hybrid models. - Executing essential parts of an ML pipeline: - Data cleaning - Leakage protection - Cross-validation design - Baseline construction - Statistical significance testing - Designing feature representations that align with the quantum component. - Profiling and improving training stability in cooperation with the quantum research team. - Contributing to internal ML libraries and SDK for future client engagements. - Supporting research and applied product development. - Translating proposed quantum machine learning algorithms into testable implementations. - Helping evaluate the measurable benefit of a quantum layer on applied tasks. Qualifications - Completed a Master's degree in computer science, applied mathematics, data science, statistics, engineering, physics, or equivalent subject. - Hands-on experience with classical machine learning through coursework, internships, or research projects. - Strong command of Python and the standard data science stack (NumPy, pandas, scikit-learn). - Experience with at least one deep learning framework (PyTorch or TensorFlow). - Comfort with classical ML toolkit including tree-based methods, gradient boosting, and kernel methods. - Experience designing rigorous experiments and reporting results with appropriate uncertainty. - Software engineering fundamentals: version control with Git, testing, reproducible environments. - Curiosity about quantum computing and willingness to learn necessary quantum concepts. - Familiarity with at least one applied ML vertical (time series forecasting, NLP, computer vision, or industrial optimisation) is a plus. - Goal-oriented and analytical, with the ability to work independently and as part of a team. - Proficiency in written and spoken English. - Legal right to live and work in the European Union or Switzerland. Requirements - Applicants must have the legal right to live and work in the European Union or Switzerland. - Unfortunately, we are unable to offer visa sponsorship for this role. Benefits - Opportunity to work with leading minds in the field of Quantum Technologies. - Gain knowledge of cutting-edge technology developments in science & engineering. - Chance to be part of one of Europe’s leading technology firms. - Welcoming, friendly, and professional colleagues. - Personal development plan with clear goals for advancement. - Competitive salary. - Flexible working arrangements. - Diverse and supportive atmosphere encouraging innovation and initiative. Company Description Quantum technologies have the potential to solve some of the world’s biggest challenges. At Terra Quantum, we are building the world’s leading Quantum Technology company, offering world-class quantum technology expertise organized as “quantum-as-a-service.” - Hybrid quantum algorithms, quantum compute, and quantum-enabled security solutions. - Access to a unique technology platform through the proprietary quantum cloud. - Focus on solving real-world challenges in machine learning, optimization, and simulation. - Committed to pioneering quantum technologies for positive global change. - Equal opportunities employer, committed to diversity, inclusion, and employee well-being.