Latinx in AI (LXAI)
Sr Principal Machine Learning Engineer
Latinx in AI (LXAI), Pleasanton, California, United States, 94566
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Sr Principal Machine Learning Engineer
role at
Latinx in AI (LXAI) .
About the Role We are seeking a highly skilled Machine Learning Engineer to contribute to a cross‑functional team building transformative AI agents for HR & Finance. This role is crucial in implementing tooling strategies, staying informed about industry trends, and ensuring our AI‑driven solutions integrate effectively within the Workday stack. You will be responsible for implementing AI frameworks, contributing to agent workflow orchestration, utilizing LLMs, agent frameworks, and enterprise AI to design and develop scalable, reliable, and trusted AI agents for both HR and Finance.
Key Responsibilities
Collaborate with a team of innovative engineers to deliver AI‑powered agents that integrate deeply into HR and Financial workflows, accelerating intelligent decision making.
Develop relationships with software engineers, machine learning engineers, and data scientists on partner teams.
Apply understanding of the AI system lifecycle, including problem definition, data acquisition, model training, system integration, and validation.
Implement and integrate AI tools, frameworks, and platforms to ensure scalability, efficiency, and compliance.
Stay up to date with advancements in AI, LLMs, RAG, autonomous agents, and orchestration frameworks to drive innovation.
Work with product, engineering, and data science teams to implement AI‑based automation solutions that enhance HR and financial operations.
Collaborate with external AI vendors, cloud providers, and open‑source communities to integrate best‑in‑class technologies into our AI stack.
Contribute to establishing monitoring, feedback loops, and continuous learning mechanisms to improve agent performance over time.
Basic Qualifications – Sr Principal
15+ years experience in data science, machine learning engineering, or a related software development team building applied machine learning products at scale, including taking products through applied research, design, implementation, production, and production‑based evaluation.
5+ years of professional experience with machine learning and deep learning frameworks & toolkits such as PyTorch and TensorFlow.
7+ years of professional experience building services to host machine learning models in production at scale.
3+ years of demonstrated experience working with large language models (LLMs), text generation models, and/or graph neural network models for real‑world use cases.
7+ years of proven experience with cloud computing platforms (e.g., AWS, GCP).
Proven track record of successfully leading, mentoring, and/or managing ML engineering teams, taking ownership of development lifecycle and sprint planning; fostering a culture of collaboration, transparency, innovation, and continuous improvement.
Bachelor’s degree in engineering, computer science, physics, math or equivalent (Master’s or PhD preferred).
Basic Qualifications – Principal
10+ years experience in data science, machine learning engineering, or a related software development team building applied machine learning products at scale.
4+ years of professional experience with machine learning and deep learning frameworks & toolkits such as PyTorch and TensorFlow.
6+ years of professional experience building services to host machine learning models in production at scale.
3+ years of demonstrated experience working with LLMs, text generation models, and/or graph neural network models for real‑world use cases.
6+ years of proven experience with cloud computing platforms (e.g., AWS, GCP).
Proven track record of successfully leading, mentoring, and/or managing ML engineering teams, taking ownership of development lifecycle and sprint planning.
Bachelor’s degree in engineering, computer science, physics, math or equivalent (Master’s or PhD preferred).
Other Qualifications
Stay up to date with advancements in AI, LLMs, RAG, autonomous agents, and orchestration frameworks to drive innovation.
Deep understanding of statistical analysis, unsupervised and supervised machine learning algorithms, and natural language processing for information retrieval and/or recommendation system use cases.
Professional experience in independently solving ambiguous, open‑ended problems and technically leading teams.
Excellent interpersonal and communication skills, with the ability to build strong relationships across teams and stakeholders.
Pay Transparency Statement The annualized base salary ranges for the primary location and any additional locations are listed below. Workday pay ranges vary based on work location. As part of the total compensation package, this role may be eligible for the Workday Bonus Plan or a role‑specific commission/bonus, as well as annual refresh stock grants. Recruiters can share more detail during the hiring process. Each candidate’s compensation offer will be based on multiple factors including, but not limited to, geography, experience, skills, job duties, and business need, among other things. For more information regarding Workday’s comprehensive benefits, please click here.
Primary Location: USA, CA, Pleasanton Base Pay Range: $268,000 USD – $402,000 USD
Additional US Location(s) Base Pay Range: $226,500 USD – $402,000 USD
Additional Considerations: If performed in Colorado, the pay range for this job is $238,400 - $357,600 USD based on min and max pay range for that role if performed in CO.
Application deadline for this role: 10/31/2025.
Approach to Flexible Work With Flex Work, we’re combining the best of both worlds: in‑person time and remote. Our approach enables our teams to deepen connections, maintain a strong community, and do their best work. You’ll have the freedom to create a flexible schedule that caters to your business, team, and personal needs, while being intentional to make the most of time spent together. Those in our remote “home office” roles also have the opportunity to come together in our offices for important moments that matter.
EEO Statement Workday is an Equal Opportunity Employer, including individuals with disabilities and protected veterans. Pursuant to applicable Fair Chance law, Workday will consider for employment qualified applicants with arrest and conviction records.
Workday will never ask candidates to apply to jobs through websites that are not Workday Careers. Please be aware of sites that may ask you to input your data in connection with a job posting that appears to be from Workday but is not. Workday will never ask candidates to pay a recruiting fee, or pay for consulting or coaching services, in order to apply for a job at Workday.
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Sr Principal Machine Learning Engineer
role at
Latinx in AI (LXAI) .
About the Role We are seeking a highly skilled Machine Learning Engineer to contribute to a cross‑functional team building transformative AI agents for HR & Finance. This role is crucial in implementing tooling strategies, staying informed about industry trends, and ensuring our AI‑driven solutions integrate effectively within the Workday stack. You will be responsible for implementing AI frameworks, contributing to agent workflow orchestration, utilizing LLMs, agent frameworks, and enterprise AI to design and develop scalable, reliable, and trusted AI agents for both HR and Finance.
Key Responsibilities
Collaborate with a team of innovative engineers to deliver AI‑powered agents that integrate deeply into HR and Financial workflows, accelerating intelligent decision making.
Develop relationships with software engineers, machine learning engineers, and data scientists on partner teams.
Apply understanding of the AI system lifecycle, including problem definition, data acquisition, model training, system integration, and validation.
Implement and integrate AI tools, frameworks, and platforms to ensure scalability, efficiency, and compliance.
Stay up to date with advancements in AI, LLMs, RAG, autonomous agents, and orchestration frameworks to drive innovation.
Work with product, engineering, and data science teams to implement AI‑based automation solutions that enhance HR and financial operations.
Collaborate with external AI vendors, cloud providers, and open‑source communities to integrate best‑in‑class technologies into our AI stack.
Contribute to establishing monitoring, feedback loops, and continuous learning mechanisms to improve agent performance over time.
Basic Qualifications – Sr Principal
15+ years experience in data science, machine learning engineering, or a related software development team building applied machine learning products at scale, including taking products through applied research, design, implementation, production, and production‑based evaluation.
5+ years of professional experience with machine learning and deep learning frameworks & toolkits such as PyTorch and TensorFlow.
7+ years of professional experience building services to host machine learning models in production at scale.
3+ years of demonstrated experience working with large language models (LLMs), text generation models, and/or graph neural network models for real‑world use cases.
7+ years of proven experience with cloud computing platforms (e.g., AWS, GCP).
Proven track record of successfully leading, mentoring, and/or managing ML engineering teams, taking ownership of development lifecycle and sprint planning; fostering a culture of collaboration, transparency, innovation, and continuous improvement.
Bachelor’s degree in engineering, computer science, physics, math or equivalent (Master’s or PhD preferred).
Basic Qualifications – Principal
10+ years experience in data science, machine learning engineering, or a related software development team building applied machine learning products at scale.
4+ years of professional experience with machine learning and deep learning frameworks & toolkits such as PyTorch and TensorFlow.
6+ years of professional experience building services to host machine learning models in production at scale.
3+ years of demonstrated experience working with LLMs, text generation models, and/or graph neural network models for real‑world use cases.
6+ years of proven experience with cloud computing platforms (e.g., AWS, GCP).
Proven track record of successfully leading, mentoring, and/or managing ML engineering teams, taking ownership of development lifecycle and sprint planning.
Bachelor’s degree in engineering, computer science, physics, math or equivalent (Master’s or PhD preferred).
Other Qualifications
Stay up to date with advancements in AI, LLMs, RAG, autonomous agents, and orchestration frameworks to drive innovation.
Deep understanding of statistical analysis, unsupervised and supervised machine learning algorithms, and natural language processing for information retrieval and/or recommendation system use cases.
Professional experience in independently solving ambiguous, open‑ended problems and technically leading teams.
Excellent interpersonal and communication skills, with the ability to build strong relationships across teams and stakeholders.
Pay Transparency Statement The annualized base salary ranges for the primary location and any additional locations are listed below. Workday pay ranges vary based on work location. As part of the total compensation package, this role may be eligible for the Workday Bonus Plan or a role‑specific commission/bonus, as well as annual refresh stock grants. Recruiters can share more detail during the hiring process. Each candidate’s compensation offer will be based on multiple factors including, but not limited to, geography, experience, skills, job duties, and business need, among other things. For more information regarding Workday’s comprehensive benefits, please click here.
Primary Location: USA, CA, Pleasanton Base Pay Range: $268,000 USD – $402,000 USD
Additional US Location(s) Base Pay Range: $226,500 USD – $402,000 USD
Additional Considerations: If performed in Colorado, the pay range for this job is $238,400 - $357,600 USD based on min and max pay range for that role if performed in CO.
Application deadline for this role: 10/31/2025.
Approach to Flexible Work With Flex Work, we’re combining the best of both worlds: in‑person time and remote. Our approach enables our teams to deepen connections, maintain a strong community, and do their best work. You’ll have the freedom to create a flexible schedule that caters to your business, team, and personal needs, while being intentional to make the most of time spent together. Those in our remote “home office” roles also have the opportunity to come together in our offices for important moments that matter.
EEO Statement Workday is an Equal Opportunity Employer, including individuals with disabilities and protected veterans. Pursuant to applicable Fair Chance law, Workday will consider for employment qualified applicants with arrest and conviction records.
Workday will never ask candidates to apply to jobs through websites that are not Workday Careers. Please be aware of sites that may ask you to input your data in connection with a job posting that appears to be from Workday but is not. Workday will never ask candidates to pay a recruiting fee, or pay for consulting or coaching services, in order to apply for a job at Workday.
#J-18808-Ljbffr