Data Scientist - ML Platforms

Company Description

Join Syngenta Group, a leader in agricultural innovation where technology meets purpose. As digital pioneers in AgTech, we're integrating AI across our value chain from smart breeding to precision agriculture. Our global team of 56,000 professionals is transforming sustainable farming worldwide. At Syngenta IT & Digital, your expertise will directly impact food security and shape the future of agriculture through cutting-edge technology.

Website address - https://www.syngentagroup.com/

Job Description

As a Data Scientist in our MLOps Platform Engineering team, you will contribute to AI Enablement by building and operating production-grade machine learning and LLM systems. You will collaborate with cross-functional teams to implement scalable data pipelines, training and fine-tuning workflows, model orchestration, inference mechanisms, and monitoring/evaluation solutions for both classical ML and modern LLM applications.

Responsibilities

• Design and implement scalable, maintainable data pipelines for ingestion, transformation, model training, and retraining under established architectural patterns.
• Implement orchestration frameworks for ML/LLM and support hybrid model deployment at scale.
• Develop and scale inference services and retrieval-augmented generation (RAG) systems.
• Integrate with various Internal/External APIs, embeddings, and data connectors
• Drive monitoring, observability, evaluation, and explainability for machine learning and LLM systems.
• Contribute towards building robust CI/CD pipelines using standard DevOps/MLOps practices.
• Collaborate with engineering, product, and research teams to operationalise and productionize AI/ML/LLM solutions.
• Write clear technical documentation and best practices guidelines.
• Knowledge share and contribute to developer knowledge forums
  
  

Must-Have Skills And Experience

• 5+ years in Data Science, ML Engineering, or related roles, with hands-on experience in productionizing ML/LLM solutions.
• Strong programming skills in Python; With understanding and experience with distributed computing platforms like Apache Spark, etc.
• Demonstrate a strong understanding of core machine learning algorithms and their mathematical foundations.
• Proficiency in building performant and robust data engineering pipelines (ETL/ELT) and large-scale data infrastructure (e.g., Data Lake, Data Mesh, Databricks).
• Expertise with machine learning lifecycle tools and orchestration frameworks (MLflow, Kubeflow, EKS, etc.).
• In-depth understanding and expertise in the different phases of ML Lifecycle, challenges and mitigating approaches
• Extensive experience in classical ML and LLM model development, fine-tuning, and deployment, orchestration, monitoring and observability.
• Hands-on with cloud platforms and services (AWS, Azure, GCP), including storage (S3, Data Lake), and compute.
• Deep understanding of MLOps/DevOps, including CI/CD, experiment tracking, monitoring, and version control (Git).
• Demonstrated ability to integrate multiple data types: structured, unstructured, image, voice, and geospatial.
• Demonstrate ability to integrate multimodal datasets
• Strong communication, documentation, and stakeholder management skills.
  
  

Nice-to-Have

• Experience in deploying AI/ML capabilities to front-end applications (web/mobile).
• Familiarity with RLHF, prompt engineering, PEFT/LoRa/QLoRa methods for LLM tuning.
• Appreciation for AI Agents, and their system-level interaction with ML/LLM models
• Knowledge of or experience with Graph-based approaches like Graph-RAG
  
  

Qualifications

Bachelor’s or Master’s degree in Computer Science, Statistics, Mathematics, Data Science, or a related quantitative field.

Additional Information

Note: 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, gender identity, marital or veteran status, disability, or any other legally protected status.

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