Senior Machine Learning Operations Engineer in Bucuresti

About the RoleAs a Machine Learning Operations Engineer, you will be responsible for developing and maintaining the cutting edge systems that bring our AI products to life. These technologies will be used to assess the Environmental, Social, and Governance (ESG) performance of public and private companies globally.The technologies you will develop range from training and inference pipelines, scaling and improving existing AI systems to any number of subfields that you see fit in order to help expand the capabilities of our products.Your work will ultimately help investors define their strategies leveraging ESG insights and will push companies to improve how they treat the environment, their social spheres (workforce, stakeholders, consumers, nearby communities), and their governance. As more and more companies move towards this direction we aim to have a far-reaching impact by promoting a healthy ESG mentality through novel AI technologies.Job ResponsibilitiesYou will be colaborating with a number of talented and software and AI research engineers. Your key focus is to expand and scale our existing ML systems:Develop and scale our ML systems to improve Morningstar | Sustainalytics products.Develop new CI / CD pipelinesDevelop and deploy human in the loop systemsResearch and develop techniques to train Large Language ModelsCollaborate with AI Research and Software Engineering teams to help them implement scalable production versions of our AI PoCs.Collaborate with QA Teams to ensure our products exceed the expectations of our stakeholders.Take initiative and be responsible for technical solutions to data quality and workflow challenges.Qualifications3+ years of relevant experience developing and deploying Machine Learning systemsExperience in developing CI / CD pipelines for trainning and deploying ML modelsExperience in developing scalable Machine Learning APIsBasic experience with microservices architecturesBasic experience in developing simple UIs (used for data annotation / model feedback)Effective communication skillsNice to haveExperience training and deploying large Deep Learning systems (e.g. BERT, T5, GPT2 or Large CV models)Experience in monitoring deployed ML models (e.g. check data and model quality, data drift, target drift)Experience with AWS (e.g. AWS Pipelines, SageMaker)Experience with MLOps Frameworks like Kubeflow, MLFlow, Weights & Biases, etc.Experience with ML software packages (e.g. PyTorch Lightning / Ignite, Ray)Experience implementing and scaling Docker container based solutions#LI-SM1About UsSustainalytics is a Morningstar company dedicated to responsible investment with over 25 years' experience in ESG research and ratings. With an extensive client base across asset managers, asset owners and investment banks, our mission is to provide the insights required for investors and companies to make more informed decisions that lead to a more just and sustainable global economy.As Morningstar’s ESG center of excellence we are responsible for driving both the commercial success and innovation of its ESG products as well as its overall ESG strategy.For more information, visit www.sustainalytics.com Morningstar’s hybrid work environment gives you the opportunity to work remotely and collaborate in-person each week. While some positions are available as fully remote, we’ve found that we’re at our best when we’re purposely together on a regular basis, typically three days each week. A range of other benefits are also available to enhance flexibility as needs change. No matter where you are, you’ll have tools and resources to engage meaningfully with your global colleagues.