AI and Machine Learning EngineerHewlett Packard Enterprise Development LP • United States
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AI and Machine Learning Engineer
Hewlett Packard Enterprise Development LP
- United States
- United States
À propos
We are seeking a Senior AI/ML & Innovation Engineer who will lead initiatives across the Hybrid Cloud portfolio and thrive in a challenging, fast‑paced environment. This role will work on average 2 days per week from an HPE office. Responsibilities
Develop and program integrated software algorithms to structure, analyze, and leverage structured and unstructured data in product and system applications. Work with large‑scale computing frameworks, data analysis systems, and modeling environments. Use machine learning and statistical modeling techniques to improve product/system performance, data management, quality, and accuracy. Formulate descriptive, diagnostic, predictive, and prescriptive insights/algorithms and translate technical specifications into code. Apply, optimize, and scale deep learning technologies and algorithms to enable advanced computer vision, natural language processing, and other complex problem‑solving. Document procedures for installation and maintenance, complete programming, perform testing and debugging, and define and monitor performance metrics. Translate customer requirements and industry trends into AI/ML products, solutions, and system improvement projects. Use advanced subject‑matter knowledge to solve complex business issues and serve as a recognized subject‑matter expert. Provide expertise and partnership to functional and technical project teams, and participate in cross‑functional initiatives. Exercise significant independent judgment to determine best methods for achieving objectives. Lead, mentor, and provide feedback to junior and mid‑level team members. Conduct research and stay current with the latest advancements in AI and machine learning technologies, frameworks, and algorithms. Explore and experiment with cutting‑edge techniques to solve complex problems and improve existing models. Collaborate with cross‑functional teams to understand business requirements and design AI and machine learning solutions. Determine appropriate algorithms, models, and frameworks; architect the overall system to ensure scalability, efficiency, and robustness. Develop, implement, and optimize machine learning models and algorithms, including data pre‑processing, feature engineering, model selection, hyperparameter tuning, and training on large datasets. Continuously monitor and improve model performance and accuracy. Deploy machine learning models into production environments, considering scalability, performance, and security. Integrate models with existing software systems and infrastructure, ensuring smooth operation and interoperability. Monitor deployed models, collect relevant metrics, analyze data, and identify areas for improvement. Fine‑tune models, optimize algorithms, and enhance system performance based on insights from monitoring and analysis. Organize and lead comprehensive design review sessions, driving discussions to align with project requirements and best practices. Work collaboratively with the engineering manager and team lead to set design and implementation standards, ensuring continuous improvement and alignment with project goals. Lead meetings to foster a collaborative and productive team environment. Deliver strategic presentations and reports to senior stakeholders, demonstrating a deep understanding of technical and business aspects. Apply data mining, data modeling, natural language processing, and machine learning to extract and analyze information from datasets. Qualifications
Bachelor’s or master’s degree in computer science, engineering, data science, machine learning, artificial intelligence, or a closely related quantitative discipline. Typically 4–7 years’ experience in AI/ML engineering. Deep understanding of machine learning algorithms such as linear regression, decision trees, support vector machines, random forests, deep learning models (neural networks), and reinforcement learning. Proficiency in model selection, hyperparameter tuning, and evaluating model performance using appropriate metrics. Strong foundation in mathematics and statistics, including linear algebra, calculus, probability theory, and statistical concepts. Proficiency in programming languages such as Python, R, or Java. Experience developing production‑level code and familiarity with software engineering best practices, version control systems (e.g., GitHub), and software development methodologies. Knowledge of libraries and frameworks like TensorFlow, PyTorch, sci‑kit‑learn, and Keras. Proficiency with GitHub CoPilot, Cursor, N8N, vibe coding, Windsurf, and similar technologies. Experience in Cloud Infrastructure (AWS, Azure, etc.). Knowledge of open‑source software, Linux, and related ecosystems. Understanding of DevOps, SRE, and MLOps practices. Advanced knowledge of deep learning architectures (CNN, RNN, transformers) and techniques such as transfer learning, generative models, and optimization algorithms. Active engagement with the latest AI and machine learning research advancements. Excellent communication skills for collaboration with cross‑functional teams and stakeholders. Strong problem‑solving and critical‑thinking abilities to guide projects and solve complex technical challenges. Benefits
Health & Well‑being: comprehensive benefits supporting physical, financial, and emotional wellbeing. Personal & Professional Development: programs to advance career goals, whether becoming a knowledge expert or applied skillset in other divisions. Unconditional Inclusion: inclusive culture that values and celebrates individual uniqueness. Hybrid work flexibility: average of two days in the office, remaining days remote. Equal Employment Opportunity Statement
Hewlett Packard Enterprise is an Equal Employment Opportunity/Veteran/Disabled/LGBT employer. We do not discriminate on the basis of race, gender, or any other protected category, and all decisions are made on the basis of qualifications, merit, and business need. HPE complies with all applicable laws related to the use of arrest and conviction records, and considers qualified applicants with criminal histories. We provide equal opportunity to all employees and applicants regardless of sex, gender, color, race, ethnicity, religion, creed, national origin, ancestry, citizenship, age, marital status, sexual orientation, gender identity, disability, pregnancy, protected veteran status, familial status, genetic information, or political affiliation. Recruitment Fraud Alert
Please note that HPE, its subsidiaries, affiliates, and authorized recruitment agencies will never charge a candidate a registration or hiring fee, and will never request personal information such as bank account details, Social Security numbers, or national IDs via social media or chat applications. All legitimate job opportunities will come through official company channels.
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Compétences linguistiques
- English
Avis aux utilisateurs
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