Role Description Estamos à procura de um(a) Machine Learning Engineer para integrar uma equipa tecnológica focada no desenvolvimento e operacionalização de soluções de Machine Learning em ambientes cloud-native. Esta função terá um papel central na construção de pipelines de ML escaláveis, automação de workflows e implementação de boas práticas de MLOps, garantindo soluções robustas e preparadas para produção. Como Machine Learning Engineer, serás responsável pelo desenho, desenvolvimento e otimização de sistemas de Machine Learning em produção, com forte foco em feature engineering, automação e escalabilidade. Irás colaborar com equipas de Data Science, Engenharia e Produto para transformar modelos analíticos em soluções produtivas, fiáveis e eficientes. Terás também um papel ativo na definição de práticas de MLOps, monitorização e melhoria contínua das plataformas de ML. Responsibilities - Desenvolver pipelines escaláveis de feature engineering; - Construir e orquestrar pipelines end-to-end de Machine Learning utilizando Databricks; - Implementar workflows de MLOps, incluindo CI/CD para Machine Learning; - Gerir o ciclo de vida dos modelos (versionamento, deployment, monitorização e retraining); - Otimizar performance, escalabilidade e custos de pipelines e modelos; - Colaborar com equipas multidisciplinares na industrialização de soluções de Data Science; - Garantir fiabilidade, monitorização e observabilidade dos sistemas de ML em produção; - Promover boas práticas de automação e engenharia de Machine Learning. Qualifications - Formação superior em Engenharia Informática, Matemática, Estatística ou área similar; - Mínimo de 5 anos de experiência em Machine Learning Engineering; - Forte experiência em feature engineering e desenvolvimento de pipelines de dados; - Experiência prática com Databricks e orquestração de workflows; - Conhecimentos sólidos de MLOps e automação; - Experiência em gestão do ciclo de vida de modelos de ML; - Capacidade comprovada de otimização de performance de modelos e pipelines; - Experiência com plataformas cloud, preferencialmente AWS; - Forte domínio de Python; - Capacidade de trabalhar de forma autónoma e colaborativa. Preferred Qualifications - Experiência em processamento distribuído de dados em larga escala; - Conhecimentos adicionais de GCP ou Azure; - Familiaridade com ferramentas de monitorização e observabilidade para ML; - Forte capacidade analítica e resolução de problemas; - Experiência em ambientes cloud-native modernos. Benefits - Regime totalmente remoto a partir de Portugal; - Participação em projetos avançados de Machine Learning e Data Engineering; - Integração numa equipa técnica especializada e colaborativa; - Ambiente orientado à inovação, automação e melhoria contínua; - Oportunidades de crescimento técnico e evolução profissional; - Contacto com tecnologias modernas de ML, cloud e MLOps; - Pacote salarial competitivo, ajustado à experiência.

Role Description We are seeking a Machine Learning Scientist to join the Enchant team at Iambic Therapeutics. Our mission is to deliver better medicines through innovation in AI-based discovery technologies. In this role, you will research, develop, and scale Enchant — our multimodal transformer model trained on a wide variety of biomedical data — pushing the boundaries of what large-scale foundation models can achieve in drug discovery. This role spans architecture research through to production deployment. - Research and implement architectural improvements to large-scale multimodal transformer models for biomedical applications - Investigate hybrid modeling approaches that combine learned representations with domain-informed structure or inductive biases - Optimize training pipelines for efficiency, stability, and scalability across many-GPU clusters - Develop and apply inference optimization techniques to support deployment in interactive discovery workflows - Design and maintain benchmarking and evaluation frameworks that track model quality across modalities and downstream tasks - Collaborate with ML and software engineering colleagues to deploy and operationalize models - Partner with computational chemists, medicinal chemists, and biologists to ensure model development is grounded in drug discovery needs - Communicate results to internal teams, external partners, and at conferences - Write high-quality research and engineering code: refactor, test, document, and package ML components to support team velocity - Depending on level: - Mentor interns and junior team members through technical guidance, code reviews, and best practices in ML experimentation - Contribute to the strategic research roadmap for Enchant and related multimodal technologies Qualifications - Required: - MS in ML/CS or a computational STEM field with relevant industry or research experience, or PhD or equivalent industry experience demonstrating comparable depth - Strong Python and PyTorch experience, including implementing and training deep learning models end-to-end - Demonstrated experience training transformer models at scale - Strong engineering habits: reproducible experimentation, clean code, testing, and performance-minded debugging - Comfort working with modern ML infrastructure (e.g., Docker, CUDA, Kubernetes, experiment tracking such as Weights & Biases) - Desired: - Experience with multimodal or multi-task model architectures - Training and inference optimization (e.g., mixed precision, kernel optimization, quantization, distributed strategies) - Familiarity with biomedical, chemical, or biological data domains - Distributed training at scale - HPC or large-scale training operations experience Location - Remote (US or UK) - On-site available in Bristol, UK and Boston, US Benefits - Industry leading competitive pay - Company paid healthcare - Flexible spending accounts - Voluntary life insurance - 401K matching - Uncapped vacation - Brand-new state-of-the-art facility in beautiful San Diego with an onsite gym and dining - Easy access to great places to live and play

• Implement ML standards, processes and best practices • Collaborate with stakeholders to identify and plan for enterprise ML portfolio needs • Guide ML team members on their deliverables and activities • Translate complex requirements into well-scoped machine learning projects • Develop machine learning applications according to requirements • Ensure machine learning solutions are scalable to meet enterprise requirements • Work closely with data scientists and data engineers to guide development of machine learning models • Create metrics to continuously evaluate the performance of machine learning solutions • Extend existing machine learning libraries and frameworks as needed • Execute own project tasks with urgency and to a high level of quality • Communicate status clearly and effectively using departmental project management tools • Follow time-tracking and other project management requirements • Participate actively in project meetings, stand-ups, etc. • Serve as technical lead for moderately complex projects, collaborating with project managers to ensure project scope/risk/budget/etc. are adequately managed • Lead project meetings and workgroups

Role Description The Applied Machine Learning group at Redfin works towards redefining real estate in the customer’s favor using machine learning. We work on foundational problems in the real estate space including recommendations (“Where should I live?”) and price estimation (“How much is a home worth?”). - You will productionize models by converting research-grade code into performant, clean, and maintainable production systems. - You will implement MLOps best practices, including CI/CD for machine learning, automated retraining pipelines, and robust model versioning. - You will optimize models for inference to ensure high-speed performance and efficiency in real-time environments. - You will monitor models in production, proactively identifying and mitigating issues related to data drift, concept drift, and system latency. - You will co-create the next generation of data-driven insights for automated valuation models (AVM) and recommender systems. - You will identify and implement iterative improvements to the machine learning models that power production-scale, customer-facing experiences. - You will serve as a technical bridge, assisting other engineers and stakeholders in understanding and applying data science methodologies and findings across the organization. - You will build data products and analytical tools that drive critical business metrics and revenue growth, directly impacting the home buying and selling experience. Qualifications - You have 5+ years of software engineering experience, with at least 2 years specifically focused on deploying and scaling machine learning models in production environments. - You are highly proficient in Python and capable of writing production-grade, modular code. - You possess a deep understanding of the end-to-end ML lifecycle, including training versus inference workflows, feature stores, and model versioning. - You are competent with ML frameworks such as PyTorch, TensorFlow, or Scikit-learn. - You are competent with monitoring, observability, and production maintenance. - You have hands-on experience with Docker and Kubernetes. - You have experience implementing model monitoring and operational rigor, including tracking data drift and latency. - You are proficient in SQL and familiar with distributed data processing tools like Spark or Kafka. Benefits - Health and well-being support for you and your family. - Peace of mind through various perks and health benefits. - Annual bonus and incentives. - Medical, dental, and vision benefits. - 401K retirement plan. - Paid-time off. Company Description Redfin is revolutionizing the $75 billion real estate industry. We use data, beautiful software, and innovative design to put customers first at every step in the home-buying and selling process.