ML Engineer

At Syngenta our goal is to build the most collaborative and trustworthy team in agriculture providing top-quality seeds and innovative crop protection solutions that improve farmers success. To support this mission Syngentas Seeds P&S is seeking a ML Engineer in Pune.The Machine Learning Engineer designs develops and operationalizes scalable machine learning solutions that drive business value. This role requires end-to-end ownership of ML pipelinesfrom data ingestion and feature engineering to model training deployment monitoring and optimization. The ideal candidate combines strong software engineering practices with deep ML expertise.

Data Engineering & Feature Development: Build and maintain robust ETL/ELT pipelines using Databricks and PySpark. Design and implement feature engineering workflows; leverage Databricks Feature Store for reusability.

Model Development & Experimentation: Develop ML models (regression classification clustering time-series NLP) using scikit-learn XG Boost Light GBM PyTorch/TensorFlow. Conduct hyperparameter tuning and model selection using ML flow for experiment tracking and reproducibility.

ML Ops & Production Deployment: Deploy models to production using Databricks Model Serving AWS Sage Maker (if applicable) or custom Fast API/Flask endpoints. Implement CI/CD pipelines for automated testing validation and deployment (GitHub Actions Jenkins GitLab CI).

Monitoring & Maintenance: Set up model monitoring dashboards to track performance data drift and concept drift. Implement alerting systems for anomalies errors and SLA breaches.

Collaboration & Documentation: Partner with data scientists analysts product managers and software engineers to translate business problems into ML solutions. Document architecture workflows model decisions and trade-offs (accuracy vs. latency vs. cost).

Core Technical Skills:

Databricks: PySpark Delta Lake Databricks SQL Feature Store ML flow integration cluster optimization.

ML flow: Experiment tracking model registry model versioning deployment workflows.

SQL: Complex queries window functions CTEs query optimization database design.

Python: Expert-level proficiency in Pandas NumPy Polars scikit-learn XG Boost Light GBM PyTorch/TensorFlow.

Version Control: Git GitHub/GitLab workflows branching strategies pull requests.

Qualifications :

Required Qualifications:

Education: Bachelors or Masters in Computer Science Data Science Statistics Engineering or related field.

Experience: 35 years in ML engineering data engineering or software engineering with ML focus.

Desired Qualifications:

Certifications: Databricks Certified Machine Learning Professional AWS Certified Machine Learning Specialty (optional).

Domain Knowledge: Experience in agriculture life sciences or related industries (for Syngenta context).

Advanced Skills: Distributed training Kubernetes real-time streaming ML LLMs/Transformers (Hugging Face)

Additional Information :

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. 

#LI-Hybrid

Remote Work :

No

Employment Type :

Full-time