Machine Learning Engineer

Key Skills

Java Programming, Python Programming, SQL, AWS, GoLang, Scala Programming, Natural Language Processing (NLP), Kaggle

Job Description

The Data Science & AI group in Personal System Software is responsible for delivering a broad range of software capabilities, including generating actionable insights from business data, increasing operational efficiency with automation, and building breakthrough experiences for HP products and services. We are seeking Machine Learning engineer to collaborate with our software engineers and product teams to solve difficult technical problems and develop new machine learning capabilities that will impact upcoming HP products. If you have deep technical skills, are intensely curious, and like to attack the hardest and the most challenging problems, want to make a difference in the lives of others, and want to work in a highly supportive environment, then we invite you to apply to join our team.

In this highly visible role, you will:

• Work in all phases of building, deploying, and evaluating machine learning applications
• Lay the foundation for new products and services by developing new technical solutions to difficult problems.
• Work in a cross-functional team environment.
• Communicate your results internally within Personal System software.

Some of our areas of interest include:

(1) Recommendation systems, including content customization and customer engagement improvement

(2) Predictive Analytics, including failure prediction, time-series forecasting, anomaly detection, and root cause analysis

(3) Natural Language Processing, including sentiment analysis, text summarization, and conversational interfaces

(4) MLOps, along with integration with software development lifecycles and continuous integration/continuous delivery

Responsibilities

• Mines data using modern tools and programming languages.
• Defines and implements models to uncover patterns and predictions creating business value and innovation.
• Identify AI opportunities, hands-on prototype and iterate models and deploy them across millions of devices.
• Comfortable with hands-on, day-to-day problem solving, implementing quick and effective action plans to meet short-term priorities and emerging opportunities.
• Works with the business and product management to understand the business domain perspective and product vision
• Balance the business needs with technical constraints by building deep subject matter expertise for your area.
• Effectively tells stories with the data using visualization tools/methods to demonstrate insight impact and business value.
• Assures accuracy, integrity, and compliance of cleansed data.
• Maintains proficiency within the data science domain by keeping up with technology and trend shifts.
• Leads a project team of data science professionals, assuring insights are communicated regularly and effectively, reviewing designs, models, accuracy, and data compliance.
• Maintain the team's focus on strategy and goal-oriented results when tackling complex problems.
• Collaborates and communicates with the project team regarding project progress and issue resolution.
• Represents the data science team for all phases of larger and more-complex development projects.
• Provides guidance, training, and mentoring to less experienced staff members.

Knowledge & Skills

Minimum:

• Extensive experience using statistics, mathematics, algorithms, and programming languages.
• Possess a background in linear algebra, statistics, or multivariate calculus.
• Expert knowledge of SQL, Python and PySpark
• Strong understanding of classical ML techniques and time-series forecasting.
• Fluent in structured and unstructured data, its management, and modern data transformation methodologies
• Understands data management principles along with model evaluation and training techniques for neural networks.
• High EQ, ability to deal with ambiguity and work collaboratively in a high paced environment.
• Enjoys working in a geographically distributed environment
• Ability to create models to pull valuable insights from data.
• Create stories and visualizations to describe and communicate data insights in a clean and simple manner.
• Ability to use creativity to spot trends and tease out patterns in large datasets.
• Hands-on technical skills with the inquisitiveness to learn products, work with them, and provide recommendations to drive continuous improvement.
• Strong analytical and problem-solving skills.
• Excellent written and verbal communication skills; mastery in English and local language.
• Able to work independently yet collaborate cross-functionally in a global and multicultural environment
• Able to manage multiple work streams effectively and provide timely updates to leadership
• Comfortable and effective working in new areas that require experimentation and rapid problem solving

Preferred:

• Experience in one or more deep learning frameworks such as Tensorflow/Keras, or PyTorch.
• Conversant in programming languages such as Golang, Java, or Scala
• In-depth knowledge of one or more deep learning areas such as computer vision or natural language processing
• Experience in Cloud computing specially AWS
• History of contributions to open source projects such as projects hosted on GitHub, SourceForge, or OSDN.
• Prior participation in data science competitions such as Kaggle, DrivenData, or CodaLab.

Scope & Impact

• Collaborates with peers, junior engineers, data scientists, and project team.
• Typically interacts with high-level Individual Contributors, Managers, and Program Teams.
• Leads a project requiring data engineering solutions development.

Education & Experience

• Master's or PhD degree in a highly quantitative field (Computer Science, Machine Learning, Operational Research, Statistics, Mathematics, or equivalent.)
• 4+ years of industry experience in predictive modelling and data science roles.

Where legally permitted, an offer of employment is conditional upon you providing proof that you are fully vaccinated against COVID-19 (as defined by the CDC) as of your first day of employment.