AI and Machine Learning Engineer III

Job description

AI and Machine Learning Engineer III This role has been designed as Hybrid with an expectation that you will work on average 2 days per week from an HPE office. Our **HPE marketing teams** are focused on making our brand easy to understand and easy to buy. We re devising data driven brand strategy, from architecture and naming, to why we exist, what we do, who we are and how we look, feel and sound. As a team, we are retaining and attracting new customers by accelerating our business strategy by making our brand stronger, more relevant, differentiated, and authentic. Join us redefine what s next for you. ***Job Family Definition:*** Develops and programs integrated software algorithms to structure, analyze and leverage structured and unstructured data in product and systems applications. Can work with large scale computing frameworks, data analysis systems, and modeling environments. Uses machine learning and statistical modeling techniques to improve product/system performance, data management, quality, and accuracy. Formulates descriptive, diagnostic, predictive and prescriptive insights/algorithms and translates technical specifications into code. Applies, optimizes and scales deep learning technologies and algorithms to give computers the capability to visualize, learn and respond to complex situations. Documents procedures for installation and maintenance, completes programming, performs testing and debugging, defines and monitors performance metrics. Contributes to the success of HPE by translating customer requirements and industry trends into AI/ML products, solutions, and systems improvement projects. ***Management Level Definition:*** Contributions include applying developed subject matter expertise to solve common and sometimes complex technical problems and recommending alternatives where necessary. Might act as project lead and provide assistance to lower level professionals. Exercises independent judgment and consults with others to determine best method for accomplishing work and achieving objectives. **What you ll do:** ***Responsibilities:*** - Responsible for conducting advanced research in AI and machine learning. This includes staying up to date with the latest advancements in the field, exploring emerging technologies, and identifying opportunities to apply cutting-edge techniques to solve complex business problems. - Tasked with designing and architecting AI solutions for complex problems. This involves analyzing business requirements, understanding constraints, and proposing appropriate machine learning models and algorithms. - Responsible for considering scalability, performance, and maintainability while designing the solution. - Provides technical guidance and mentorship to junior team members. This includes sharing best practices, reviewing code and designs, and helping team members overcome technical challenges. Participate in technical discussions and provide thought leadership within the organization. - Works closely with stakeholders, such as product managers, data scientists, and business analysts, to understand their requirements and translate them into technical solutions. Collaborate with cross-functional teams to ensure alignment and successful AI and machine learning project implementation. - Responsible for driving continuous improvement and innovation in the organizations AI and machine learning practices. This involves identifying areas of improvement, exploring new techniques or technologies, and promoting the adoption of best practices. - Be involved in evaluating and integrating third-party tools or services that can enhance the capabilities of AI solutions. - Facilitates design review sessions for your projects, ensuring alignment with project requirements and best practices. - Mentor junior team members during review sessions. - Collaborates closely with the engineering manager and team lead to refine and iterating on design and implementation strategies, providing constructive feedback to peers. - Participates in and coordinates meetings, ensuring effective coordination and communication among team members. - Independently prepares and delivers detailed presentations and reports to stakeholders, translating complex technical concepts into understandable terms for non-technical audiences. - May be required to interpret and report data findings and maintain or update specific business intelligence tools, databases, dashboards, systems, or methods - May be involved in the design and development of solutions to complex application problems, system administration issues, or network concerns, where applicable to the role. **What you need to bring:** ***Education and Experience Required:*** - Bachelors degree in computer science, engineering, data science, machine learning, artificial intelligence, or closely related quantitative discipline. Master s degree is desirable. - Typically, 4-7 years experience. ***Knowledge and Skills:*** - Deep understanding of machine learning algorithms, such as linear regression, decision trees, support vector machines, random forests, deep learning models (e.g., neural networks), and reinforcement learning. Proficient in model selection, hyperparameter tuning, and evaluating model performance using appropriate metrics. - A strong foundation in mathematics and statistics. In-depth knowledge of linear algebra, calculus, probability theory, and statistical concepts. Understanding and developing complex machine learning models and algorithms. - Proficiency in programming languages such as Python, R, or Java is expected. Experience developing production-level code and familiarity with software engineering best practices, version control systems (e.g., Git), and software development methodologies are also required. Additionally, knowledge of libraries and frameworks like TensorFlow, PyTorch, sci-kit, and Keras is a plus. - Advanced knowledge and experience in deep learning. Understanding ad