招聘
Your work days are brighter here.
We’re obsessed with making hard work pay off, for our people, our customers, and the world around us. As a Fortune 500 company and a leading AI platform for managing people, money, and agents, we’re shaping the future of work so teams can reach their potential and focus on what matters most. The minute you join, you’ll feel it. Not just in the products we build, but in how we show up for each other. Our culture is rooted in integrity, empathy, and shared enthusiasm. We’re in this together, tackling big challenges with bold ideas and genuine care. We look for curious minds and courageous collaborators who bring sun-drenched optimism and drive. Whether you're building smarter solutions, supporting customers, or creating a space where everyone belongs, you’ll do meaningful work with Workmates who’ve got your back. In return, we’ll give you the trust to take risks, the tools to grow, the skills to develop and the support of a company invested in you for the long haul. So, if you want to inspire a brighter work day for everyone, including yourself, you’ve found a match in Workday, and we hope to be a match for you too.
About the Team
Are you energized by seeing AI products come to life in real-world settings—especially when they directly impact how companies plan their workforce and finances?
At Workday, our Adaptive Planning organization is on a mission to reimagine the FP&A customer journey with an AI-first attitude. We serve thousands of the world’s largest enterprises, and now we're building agentic workflows that will transform how finance teams interact with planning systems—making them more intelligent, proactive, and efficient.
We’re looking for highly creative, results-driven, and deeply technical AI/ML Engineers to help us shape the future of financial planning. If you're passionate about building real production-grade AI that solves complex business problems and delivers measurable impact—this is your team
About the Role
Are you driven to apply innovative AI to real-world enterprise challenges? As an AI/ML Engineer on the Workday Adaptive Planning team, you’ll help redefine how financial planning is done at scale—by designing and building intelligent, agentic workflows that power the next generation of FP&A solutions. You’ll be at the forefront of bringing "AI-first" thinking into production, developing enterprise level intelligent systems that automate, adapt, and assist users throughout the financial planning journey. Your work will directly impact thousands of global enterprises and millions of end users.
What You’ll Do:
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Technical leadership: lead design and development of sophisticated AI agents that reason, learn, and interact across complex business processes to enhance productivity and decision-making.
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Integrate AI Frameworks: Embed secure, scalable, and reliable agentic capabilities into core Adaptive Planning features.
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Partner Cross-Functionally: Collaborate with extraordinary engineers and product managers to bring ideas to life.
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Own Projects End-to-End: Lead the full AI development lifecycle—problem framing, data prep, design & development, deployment, evaluation, and continuous improvement.
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Leverage Rich Planning Data: Harness Workday Adaptive Planning’s vast enterprise datasets to tune and optimize your AI models for high-value outcomes.
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Mentorship: Provide technical guidance to junior engineers. Conduct critical code reviews and unblock the team on technical hurdles.
We’re looking for bold thinkers with strong technical and a product mindset. You’ll need to move fast, think big, and stay grounded in solving real customer problems through AI. If this sounds like your kind of challenge, we’d love to talk
About You
Basic Qualifications:
- 3+ years experience working on a data science, machine learning or related software development team.
- 3+ years experience with Python supporting ML/AI libraries, with experience in shipping secure, production solutions.
- 8+ years of experience in object oriented programming with Java.
- 8+ years experience in SaaS software development.
- Other Qualifications
- Bachelor's degree in a relevant field, such as Computer Science, Mathematics, or Engineering. A PhD or MS degree in a relevant field, such as Computer Science, Mathematics, or Engineering is highly desired.
- Extensive experience with large language models (LLM), retrieval augmented generation (RAG) systems, semantic search and text embedding models, vibe coding, MCP, langgraph, transformer neural networks, and related frameworks.
- Experience with cloud computing platforms (e.g. AWS, GCP), containerization technologies (e.g. Docker) and data engineering pipelines (e.g. ETL)
- Experience developing and deploying machine learning solutions using large-scale datasets, including specification design, data collection and labeling, model development, validation, deployment, and ongoing monitoring.
- You have a strong focus on delivering high-quality software products, and you value test automation and performance engineering
- An ability to balance speed with delivering high-quality, practical solutions. Shown perseverance in overcoming significant problems.
Pursuant to applicable Fair Chance law, Workday will consider for employment qualified applicants with arrest and conviction records.
Workday is an Equal Opportunity Employer including individuals with disabilities and protected veterans.
Are you being referred to one of our roles? If so, ask your connection at Workday about our Employee Referral process!
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关于Workday

Workday
PublicWorkday, Inc., is an American on‑demand (cloud-based) financial management, human capital management, and student information system software vendor.
10,001+
员工数
Pleasanton
总部位置
$45B
企业估值
评价
3.9
10条评价
工作生活平衡
3.8
薪酬
4.2
企业文化
4.1
职业发展
3.2
管理层
2.8
72%
推荐给朋友
优点
Good pay and compensation
Supportive team and culture
Flexible work arrangements
缺点
Management transparency and responsiveness issues
High stress and overwhelming workload
Limited career growth opportunities
薪资范围
12个数据点
Mid/L4
Mid/L4 · Analytics Data Specialist
1份报告
$182,132
年薪总额
基本工资
$140,109
股票
-
奖金
-
$182,132
$182,132
面试经验
9次面试
难度
3.9
/ 5
时长
14-28周
体验
正面 11%
中性 11%
负面 78%
面试流程
1
Application Review
2
Recruiter Screen
3
Hiring Manager Interview
4
Director Interview
5
Team Interviews
6
Offer Decision
常见问题
Behavioral/STAR
Past Experience
Culture Fit
Technical Knowledge
Management/Leadership
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