Lead the design, development, and deployment of production-grade AI/ML solutions that drive measurable business impact across Syngenta’s operations. You will own end-to-end ML pipelines, from problem definition through production deployment, while collaborating with cross-functional teams to transform agricultural and business challenges into scalable AI applications.
Accountabilities
- Design, develop, and deploy production ready AI/ML models and applications that solve critical business problems
- Own the complete ML lifecycle: data pipeline design, feature engineering, model training, evaluation, deployment, and monitoring
- Collaborate with cross-functional teams to understand business requirements and translate them into technical solutions
- Implement MLOps best practices including model versioning, CI/CD pipelines, and automated retraining
- Translate complex business requirements into technical AI/ML solutions with clear success metrics
- Conduct code reviews and establish engineering best practices for AI projects
- Evaluate and integrate emerging AI technologies (LLMs, GenAI, RAG systems) into Syngenta’s ecosystem
- Lead POCs and MVPs using design thinking methodologies to validate solution feasibility
- Optimize model performance, latency, and cost-efficiency for production systems
- Contribute to Syngenta’s AI platform capabilities and reusable component libraries.
Knowledge, experience & capabilities
- 3+ years of hands-on experience in AI/ML engineering or related roles
- Proven track record of deploying models to production environments
- Proficiency in Python
- Good understanding of AWS cloud architecture including Sagemaker and Bedrock
- Ability to use identify and re-use GitHub projects to solve business problems
- Experience working with cross-functional teams and translating business needs into technical solutions
- Demonstrated ability to manage multiple projects and deliver results in agile environments
Critical success factors & key challenges
- Strong algorithm design, analysis and reasoning skills
- Ability to deliver POCs, MVPs, Experiments, technology evaluations following design thinking practices
- Ability to orchestrate efforts needed to prioritize business initiatives across complex change agendas
- Excellent communication and stakeholder management skills to explain technical information to individuals who don’t have the same technical background
- Problem solving and decision-making skills
- Risk assessment and mitigation for AI/ML projects
- Proactive in identifying opportunities for AI-driven improvements
- Teamwork, team management and leadership skills
Innovations
Employee may, as part of his/her role and maybe through multifunctional teams, participate in the creation and design of innovative solutions. In this context, Employee may contribute to inventions, designs, other work product, including know-how, copyrights, software, innovations, solutions, and other intellectual assets.
