Job responsibilities You will contribute to design and drive the development of robust scalable architectures and infrastructure for deploying and managing machine learning (ML) applications, ensuring high availability, performance and securityYou will collaborate with data scientists and engineers to translate business needs into effective and efficient ML systems and applicationsYou will own the development and maintenance of core functionalities within ML applications, including ML pipelines, model training and deployment, and monitoring and evaluationYou will drive the functional stream of work by providing technical expertise, handling team discussions and ensuring timely delivery of assigned tasksYou will stay ahead of the curve by actively exploring and implementing the latest tools, frameworks and offerings in the ML landscapeYou will facilitate collaborative problem solving within the team by actively listening, communicating effectively and mentoring other engineersYou will contribute to the development and execution of the team's overall ML strategy, aligning technical capabilities with business objectivesYou will proactively identify and address challenges related to ML systems and applications, proposing solutions and implementing improvements Job qualifications Technical Skills Comfort with conversational EnglishYou have hands-on experience with on-premise and cloud services for building and deploying ML pipelines, Azure, AWS, GCP or Databricks and associated ML managed servicesYou have experience in writing clean, maintainable and testable code, demonstrating attention to refactoring and readability of the codeYou are proficient in scripting languages such as Python or Shell for automation and task streamliningYou have knowledge of distributed systems and scalable architectures to handle large-scale ML applicationsYou have experience with building, deploying, and maintaining ML systems using relevant ML techniques and platforms, Scikit-learn, Tensorflow, MLFlow, Kubeflow, PytorchYou have experience with building, deploying and maintaining ML systems and experience with application of MLOps principles and CI/CD to MLYou have experience in machine learning engineering and data science, are familiar with key ML concepts, algorithms and frameworks, and understand ML model lifecyclesYou have experience with designing and operating the infrastructure required to run different types of ML training and serving workloads, on-premise vs. cloud infrastructure, infrastructure as code, monitoring, etc. Professional Skills You understand the importance of stakeholder management and can easily liaise between clients and other key stakeholders throughout projects, ensuring buy-in and gaining trust along the wayYou are resilient in ambiguous situations and can adapt your role to approach challenges from multiple perspectivesYou don't shy away from risks or conflicts, instead you take them on and skillfully manage themYou are eager to coach, mentor and motivate others and you aspire to influence teammates to take positive action and accountability for their workYou enjoy influencing others and always advocate for technical excellence while being open to change when needed Other things to know Learning & Development There is no one-size-fits-all career path at Thoughtworks: however you want to develop your career is entirely up to you. But we also balance autonomy with the strength of our cultivation culture. This means your career is supported by interactive tools, numerous development programs and teammates who want to help you grow. We see value in helping each other be our best and that extends to empowering our employees in their career journeys. Job DetailsCountry: BrasilCity: BrasilDate Posted: 06-04-2024Industry: Information TechnologyEmployment Type: Regular
