Description -

Job Summary
• This role is responsible for specializing in development and deployment of machine learning models that drive innovation and business value. The role researches and implements appropriate ML algorithms and tools, runs machine learning tests and experiments, and trains and retrains systems when necessary. The role contributes to deploying models in production environments and ensuring their seamless integration.

Responsibilities
• Develops and programs integrated software solutions, especially in support of the development, deployment and life cycle of machine learning models.
• Trains and validates models using appropriate evaluation metrics and techniques.
• Optimizes and tunes hyperparameters to improve model performance and generalization.
• Deploys machine learning models to production environments, ensuring scalability, reliability, and efficiency.
• Monitors and maintains deployed models, making necessary updates to adapt to changing data or requirements.
• Spearheads the design of ML systems, experiments with ML algorithms, and regularly trains systems for maximum efficiency.
• Designs, develops, tests, and maintains ML pipelines that efficiently produce scalable models.
• Cooperates with CI/CD teams to ensure seamless deployment of models to production.
• Partners with research and engineering teams to enhance automated model training techniques.
• Applies machine learning and statistical modeling techniques to business or research problems.

Education & Experience Recommended
• Graduate Degree in Computer Science, Statistics, Mathematics, Data Science, or any other related discipline or commensurate work experience or demonstrated competence.
• Typically has 3-4 years of work experience, preferably in computer programming languages, machine learning, algorithms, statistical methods, or a related field or an advanced degree with 2-3 years of work experience.

Preferred Certifications
• AWS Certified Machine Learning Specialty

Knowledge & Skills
• Agile Methodology
• Algorithms
• Amazon Web Services
• Apache Spark
• Artificial Intelligence
• Automation
• Big Data
• C++ (Programming Language)
• Computer Science
• Data Science
• Deep Learning
• Java (Programming Language)
• Machine Learning
• Microsoft Azure
• Natural Language Processing
• Python (Programming Language)
• PyTorch (Machine Learning Library)
• Scikit-learn (Machine Learning Library)
• Software Engineering
• TensorFlow

Cross-Org Skills
• Effective Communication
• Results Orientation
• Learning Agility
• Digital Fluency
• Customer Centricity

Impact & Scope
• Impacts multiple teams and may act as a team or project leader providing direction to team activities and facilitates information validation and team decision making process.

Complexity
• Responds to moderately complex issues within established guidelines.

Disclaimer
• This job description describes the general nature and level of work performed in this role. It is not intended to be an exhaustive list of all duties, skills, responsibilities, knowledge, etc. These may be subject to change and additional functions may be assigned as needed by management.
 

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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 you’d like more information about HP’s 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