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HP Inc. Machine Learning Engineer and Operations in Bangalore, India

HP is the world's leading personal systems and printing company, we create technology that makes life better for everyone, everywhere. Our innovation springs from a team of individuals, each collaborating and contributing their own perspectives, knowledge, and experience to advance the way the world works and lives.

We are looking for visionaries, like you, who are ready to make a purposeful impact on the way the world works.

At HP, the future is yours to create!

Job Description

The Role

As a Machine Learning Engineer - MLOps, you will develop AI-powered software applications, especially internal business applications. You will work closely with product managers, business stakeholders, data scientists and other software engineers to design, develop, and implement cutting-edge machine learning models that are properly trained, validated, and optimized for performance. Below is a description of responsibilities, but this role will require the flexibility to adapt to other duties and responsibilities as needed

Responsibilities

  • Lead the production efforts of AI/ML solutions: architect systems that enable and ensure successful deployments, monitoring, and maintenance of ML models in production

  • Work closely with the project team (project lead, data scientists, other engineers) and with business stakeholders to understand requirements and design an AI/ML solution accordingly

  • Hands-on development of MLOps infrastructure, e.g. coding or configuring pipelines for data processing, model training, evaluation, and inference; version control; feature stores; and model stores.

  • Monitor and maintain ML models in production, troubleshooting issues where needed

  • 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

Skills and Profile

  • Prior MLOps experience: deploying, monitoring, and maintaining AI/ML applications in production

  • Prior experience creating and maintaining machine learning modeling infrastructure to enable data scientists

  • Prior experience training and evaluating machine learning models

  • Proficient in Python for developing production applications

  • Prior experience working in a distributed team with diverse backgrounds is a plus. Ability to engage in discussions in a respectful manner is a must.

  • In this team we value a start-up mindset and initiative-taking to deliver to our internal customers. The ideal candidate will have experience from a fast-moving SaaS start-up in addition to experience from a large complex organization.

  • Technologies you may use include: AzureML services, Databricks, SQL, Docker, CI/CD

  • Mastery in English is required.

Education and Length of Experience

Bachelor's degree in Computer Science or similar, or demonstrated competence, plus typically a minimum of 7-10 years of relevant experience or equivalent. Graduate level (e.g. Master's) degree preferred.

Sustainable impact is HP's commitment to create positive, lasting change for the planet, its people, and our communities. This serves as a guiding principle for delivering on our corporate vision - to create technology that makes life better for everyone, everywhere.

HP is a Human Capital Partner - we commit to human capital development and adopting progressive workplace practices in India.

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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).

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