Vaga de Machine Learning Engineer

Imagine and printing group building next generation experiences for customers is seeking an individual to join our HP R&D Brazil team as an AI/ML engineer. The candidate will research and develop Machine Learning models, generative AI models and work with other team members and business unit partners to develop proof-of-concept and product prototypes and help move technologies to product. HP R&D engineers are expected to undertake programs which will advance the state of the art and have a significant business impact for HP. The ideal candidate will have the ability to identify key issues and challenges with existing implementations and implement solutions for real-world application. Also, the candidate should be able to collaborate with other engineers, developers, strategists, and product managers on new applications. Strong communication skills are required, and the ability to drive applied research into production is highly valued. Job Summary Frequently contributes to the development of new ideas and methods. Works on complex problems where analysis of situations or data requires an in-depth evaluation of multiple factors. Leads and/or provides expertise to functional project teams and may participate in cross-functional initiatives. Acts as an expert providing direction and guidance to process improvements and establishing policies. Frequently represents the organization to customers/partners. Exercises significant independent judgment within broadly defined policies and practices to determine the best method for accomplishing work and achieving objectives. May provide mentoring and guidance to lower-level employees. Works with architects, tech leads, product, and program managers to understand the business problem. Works with software engineers to understand systems and craft interfaces to model for deployment. Interacts with teams collecting data to assist in defining collection protocols and assure data quality. Codes, trains, validates, and optimizes machine learning models, possibly utilizing new model architectures, optimization techniques or objective functions. Responsibilities Architects, develops and programs integrated software solutions, especially in support of the development, deployment, and life cycle of machine learning models. Applies machine learning and statistical modeling techniques to business or research problems. Defines collection protocols and analyzes data sources; develops, trains, and evaluates models; creates visualizations of data properties and model performance. Deploys and maintains models. Directs technical teams in achieving these objectives. Provides subject matter expertise to the rest of the team, e.g. proactively looking for opportunities to streamline the solution development process and teaching team members to use new processes or tooling. Provides guidance and mentoring to less-experienced team members in the same function. Keeps knowledge and skills current by reading state of the art research papers and blog posts from industry and research labs. Studies new methods to understanding industry trends and emerging technologies. Disseminates this knowledge within teams and across teams. Education and Experience Required Bachelor's, Master's (preferred) in Computer Science, Statistics, or equivalent. Minimum 5+ years experience on ML/AI. Knowledge and Skills Fluent in one or more Machine Learning Frameworks (e.g. Pytorch, TensorFlow, scikit-learn, etc). Fluent in Python and knowledge of one or more additional programming Languages. Technologies you may use include Azure services such as Azure Machine Learning, Azure AI Search as well as python, micro services, docker, CI/CD, Elastic Search, SQL, and NoSQL. Knowledge of modern computer science including algorithms, data structures, software architecture. Where applicable, knowledge of cloud and hybrid cloud service architectures and their impacts on development and deployment. Able to architect new solutions that combine services, data preparation and preprocessing, machine learning models and data presentation. Knowledge of the Mathematics of Machine Learning and Statistics Deep understanding of current machine learning algorithms, under which circumstances each is applicable and their pros and cons. Able to compose new model architectures and objective functions. Knowledge of data processing techniques and data preprocessing requirements for the common machine learning approaches. Knowledge of data collection techniques. Knowledge of data augmentation approaches and their pros and cons. Spoken and written English is required. Plus for LLM experience and Open AI API. Plus for search technologies and vector databases. Plus for general software engineering skills, as well as Data Science skills. Plus for experience working in a distributed team with diverse backgrounds. The recent AI progress is disruptive, and our team is in the midst of it! Therefore, day-to-day priorities, tasks, and team structure may change rapidly. We are looking for somebody who thrives in such an environment. Job - Software Schedule - Full time Shift - No shift premium (Brazil) Travel - Not Specified Relocation - Equal Opportunity Employer (EEO) - HP, Inc. provides equal employment opportunity to all employees and prospective employees, without regard to race, color, religion, sex, national origin, ancestry, citizenship, sexual orientation, age, disability, or status as a protected veteran, marital status, familial status, physical or mental disability, medical condition, pregnancy, genetic predisposition or carrier status, uniformed service status, political affiliation or any other characteristic protected by applicable national, federal, state, and local law(s). Please be assured that you will not be subject to any adverse treatment if you choose to disclose the information requested. This information is provided voluntarily. The information obtained will be kept in strict confidence. If youd like more information about HPs EEO Policy or your EEO rights as an applicant under the law, please click here: Equal Employment Opportunity is the Law Equal Employment Opportunity is the Law  Supplement