HP
Machine Learning Engineer - MLOps
HP, Austin, Texas, us, 78716
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 productionalization 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.
Provide 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.
Provide 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.
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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 productionalization 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.
Provide 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.
Provide 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.
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