AI/ML Developer

Job Description In this role, you will write in Python to deliver a wide variety of Machine Learning & Data Science solutions. Your responsibilities will include implementing models and algorithms on Databricks and H2O. You will also be building tools to accelerate feature experimentation and exploration with lineage, data privacy protection, and easier model performance debugging. Collaborating with Product Owners, you will apply Workdays agile processes and be responsible for the initiation, delivery, and communication of projects for the stakeholder organizations. Additionally, you will be building ML-as-a-service with the purpose of taking experiments to production quickly. Sharing your learnings and project findings with the wider Workday Machine Learning Community will also be part of your role. It is essential that you are willing to work across multiple time zones. **Key Responsibilities:** - Write in Python to deliver a wide variety of Machine Learning & Data Science solutions - Implement models and algorithms on Databricks and H2O - Building tools to accelerate feature experimentation and exploration with lineage, data privacy protection, and easier model performance debugging - Collaborate with Product Owners to apply Workdays agile processes and be responsible for the initiation, delivery, and communication of projects for the stakeholder organizations - Building ML-as-a-service, with the purpose of taking experiments to production quickly - Share learnings and project findings with the wider Workday Machine Learning Community - Willing to work across multiple time zones **Qualifications Required:** - Proficient experience in Python coding, SQL, Spark, and experience developing models and other data science work with Python - 3 - 4+ years of experience implementing models or machine learning algorithms in production - Experience on any of these cloud platforms (AWS, Azure, GCP) In addition to the above responsibilities and qualifications, the job also requires experience in implementing models or machine learning algorithms in production and familiarity with cloud platforms such as AWS, Azure, or GCP. In this role, you will write in Python to deliver a wide variety of Machine Learning & Data Science solutions. Your responsibilities will include implementing models and algorithms on Databricks and H2O. You will also be building tools to accelerate feature experimentation and exploration with lineage, data privacy protection, and easier model performance debugging. Collaborating with Product Owners, you will apply Workdays agile processes and be responsible for the initiation, delivery, and communication of projects for the stakeholder organizations. Additionally, you will be building ML-as-a-service with the purpose of taking experiments to production quickly. Sharing your learnings and project findings with the wider Workday Machine Learning Community will also be part of your role. It is essential that you are willing to work across multiple time zones. **Key Responsibilities:** - Write in Python to deliver a wide variety of Machine Learning & Data Science solutions - Implement models and algorithms on Databricks and H2O - Building tools to accelerate feature experimentation and exploration with lineage, data privacy protection, and easier model performance debugging - Collaborate with Product Owners to apply Workdays agile processes and be responsible for the initiation, delivery, and communication of projects for the stakeholder organizations - Building ML-as-a-service, with the purpose of taking experiments to production quickly - Share learnings and project findings with the wider Workday Machine Learning Community - Willing to work across multiple time zones **Qualifications Required:** - Proficient experience in Python coding, SQL, Spark, and experience developing models and other data science work with Python - 3 - 4+ years of experience implementing models or machine learning algorithms in production - Experience on any of these cloud platforms (AWS, Azure, GCP) In addition to the above responsibilities and qualifications, the job also requires experience in implementing models or machine learning algorithms in production and familiarity with cloud platforms such as AWS, Azure, or GCP.