Machine Learning Engineer

Company Description

Syngenta is a global leader in agriculture; rooted in science and dedicated to bringing plant potential to life. Each of our 30,000 employees in more than 90 countries work together to solve one of humanity’s most pressing challenges: growing more food with fewer resources. A diverse workforce and an inclusive workplace environment are enablers of our ambition to be the most collaborative and trusted team in agriculture.

Our employees reflect the diversity of our customers, the markets where we operate and the communities which we serve. No matter what your position, you will have a vital role in safely feeding the world and taking care of our planet. Join us and help shape the future of agriculture.

Job Description

As a Machine Learning Engineer at Syngenta, you will work within a multidisciplinary global team to discover, define, and design experiences that empower researchers to work more effectively and efficiently by utilizing our data-driven solutions. We are seeking an experienced Machine Learning Engineer to join our team and play a crucial role in developing and refining machine learning models that drive our products and services forward.

In this role, you will work directly with stakeholders and technical partners to design and implement cutting edge AI solutions that provide actionable insights to the business. The ideal candidate will have a proven track record of implementing machine learning solutions and a deep understanding of data structures, algorithms, and statistical methods. As a generalist, you are adaptable and a flexible problem solver with technical expertise, analytics skills, and product sense to successfully pivot/context-switch amongst projects with a variety of scale and complexity.

Accountabilities:

• Design, build, and maintain scalable machine learning solutions in production environments.
• Contribute across the full lifecycle of machine learning projects, including problem definition, data exploration, model selection, performance evaluation, and deployment.
• Collaborate with product managers and engineers to integrate machine learning models into user-facing products.
• Optimize existing machine learning systems for performance and scalability.
• Stay current with the latest machine learning techniques and propose adaptations and improvements to internal practices.
• Develop metrics and monitoring systems to track the performance of models and algorithms in the field.
• Communicate complex machine learning concepts to non-technical stakeholders.
• Contribute to the team's knowledge base.
• Promote a safe work environment and a strong safety culture

Qualifications

Required:

• Master's or Doctoral degree in Computer Science, Mathematics, Statistics, or a related field.
• 5-8 years of experience in a machine learning engineering role.
• Proficiency with machine learning frameworks (e.g., TensorFlow, Keras, PyTorch) and libraries (e.g., scikit-learn, XGBoost).
• Solid understanding of data structures, machine learning algorithms, and statistical methods.
• Experience with applying machine learning models to tabular data.
• Strong programming skills in Python and SQL.
• Experience with data pipeline and workflow management tools.
• Knowledge of cloud services (AWS, GCP, Azure) and containerization technologies (Docker, Kubernetes).

Additional Information

• Full Benefit Package (Medical, Dental & Vision) that starts the same day you do
• 401k plan with company match, Profit Sharing & Retirement Savings Contribution
• Paid Vacation, 9 Paid Holidays, Maternity and Paternity Leave, Education Assistance, Wellness Programs, Corporate Discounts among others
• A culture that promotes work/life balance, celebrates diversity, and offers numerous family-oriented events throughout the year

Syngenta is an Equal Opportunity Employer and does not discriminate in recruitment, hiring, training, promotion or any other employment practices for reasons of race, color, religion, gender, national origin, age, sexual orientation, marital or veteran status, disability, or any other legally protected status.

Family and Medical Leave Act (FMLA
Equal Employment Opportunity Commission's (EEOC)
Employee Polygraph Protection Act (EPPA)

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