As a Machine Learning Scientist II, you will work within a cross-functional team of engineers and product managers to develop, evaluate, and deploy GenAI-powered solutions for scalable, customer-facing applications. Your work will focus on implementing agentic capabilities, contributing to evaluation frameworks, and delivering measurable business impact through data-driven experimentation.
Key Job Responsibilities and Duties:
Contribute to the design and development of end-to-end agentic systems, ensuring code quality and efficiency in production.
Build agentic solutions for different tasks and use cases using state-of-the-art techniques
Develop and carry out evaluation strategies, including formulating new metrics and building evaluation judges
Adhere to and promote established best practices in GenAI application development within the team.
Collaborate actively with team members, participating in code reviews, sharing knowledge, and contributing to a positive team environment.
Collaborate with product managers, data scientists, and analysts to understand business requirements and translate them into ML solutions.
Conduct deep data analysis to evaluate model performance, label quality, features exploration.
Work closely with ML engineers to ensure and improve the solutions latency/throughput meets product requirements and ensure deployment of your model to production.
Qualifications & Skills:
Bachelors or masters degree in Computer Science, Engineering, Statistics, or a related field.
Minimum of 3 years of experience as a Machine Learning Scientist or a similar role, with a consistent record of successfully delivering ML solutions to production.
Strong understanding and practical experience with Generative AI models, Natural Language Processing and engineering aspects of developing ML.
Experience executing research and development plans and contributing to large-scale ML applications.
Experience on multiple ML facets: working with large data sets, model development, statistics, experimentation, data visualization, optimization, software development.
Experience collaborating cross-functionally in the development of ML products (e.g. Developers, Product Managers, UX specialists, etc.).
Strong working knowledge of Python, LangChain, SQL, and Spark or similar technologies.
Strong coding practices, including writing and reviewing production-quality, maintainable, and well-tested code, with the ability to effectively leverage modern AI coding assistants while maintaining high standards for correctness, readability, and system design.
Excellent English communication and presentation skills, both written and verbal.
