18 hours ago
Tel Aviv-Yafo, IsraelMid Level
Responsibilities
- Design, build, and improve ML-powered software products.
- Analyze and model large-scale textual data for prediction, classification, and decision-making.
- Develop and evaluate NLP and machine learning models, including relevant LLM and generative AI techniques.
- Convert data analysis and experimentation into prototypes, production-ready code, and service integrations.
- Own quality, performance, metrics, evaluation, and ongoing data-driven improvement.
- Collaborate with product, engineering, and research partners.
Requirements
- At least 4 years of experience as a machine learning engineer, data scientist, software engineer, or in a related technical role.
- Strong Python skills and experience building, shipping, and maintaining production-grade code.
- Solid software engineering fundamentals, including clean APIs, testing, CI/CD, observability, and maintainable codebases.
- Practical experience with large-scale data, data modeling, and production systems supporting data-driven products.
- Familiarity with machine learning, deep learning, and NLP concepts, with hands-on experience using PyTorch, TensorFlow, or scikit-learn.
- Bachelor's degree in Computer Science or a related field.
- A master's degree and experience with GenAI and LLMs are preferred.
Benefits
- Hybrid work in the Israeli site with three days in the office and two days from home.
- Career growth, learning, collaboration, and support from a strong technical team.
- Reasonable accommodations are available for qualified individuals during the application process.
Categories
About Workday
Workday builds cloud-based enterprise applications for human capital management and financial management, including payroll, time tracking, expenses, planning, and procurement, sold on a subscription basis with professional services. Founded in 2005 and headquartered in Pleasanton, California, it is a public company traded on NASDAQ as WDAY. Organizations worldwide use Workday to unify HR and finance data, automate processes, and apply AI to workforce and financial operations.