In this role you will design, develop, and enable scalable, reliable, and production-ready Machine Learning and GenAI solutions by translating business and technical requirements into robust ML architectures, pipelines, APIs, and deployment frameworks.
Your key responsibilities
- Provide technical recommendations and evaluate feasibility to guide the development of scalable ML solutions.
- Collect and analyze technical requirements to ensure robust and effective data science implementations.
- Design and implement scalable and maintainable ML pipeline architectures to meet performance and reliability requirements.
- Develop and optimize modular, efficient code for managing and deploying ML models across the company's platform, ensuring robust documentation and validation processes.
- Create and design APIs and interfaces for seamless integration of ML solutions with client systems.
- Develop and implement frameworks for the latest ML technologies, including agentic platforms, ensuring regular maintenance and upgrades to keep pipelines efficient and relevant.
You bring
- Expert knowledge in Python, Git, MLFlow, and AzureML.
- Strong problem-solving skills and ability to communicate effectively with non-technical partners.
- Experience in creating and maintaining scalable and robust ML pipelines as well as work with LLMs.
- Understanding of agentic platforms and the tools required to develop and implement them.
- Ability to collect and interpret technical requirements from various stakeholders.
- Skills in GenAI and modern development practices, with a commitment to continuous learning and improvement.