ML Engineer

fluor

Vadodara, IN-GJ, India 5 Years Exp Posted 32d ago

Key Responsibilities

Design, develop, and deploy machine learning models for predictive analytics, optimization, and decision support across EPC project lifecycles
Translate engineering, construction, and operations use cases into ML solutions (e.g., cost forecasting, schedule risk, quality defects, equipment reliability)
Build end-to-end ML pipelines including data ingestion, feature engineering, model training, validation, and monitoring
Collaborate with data architects to ensure scalable, secure, and compliant data and ML architectures
Apply statistical analysis and advanced ML techniques (supervised, unsupervised, time‑series, NLP where applicable)
Optimize model performance and reliability for production environments
Partner with business stakeholders to communicate insights, assumptions, and model limitations clearly
Ensure adherence to data governance, cybersecurity, and privacy standards
Support deployment using CI/CD and MLOps best practices
Mentor junior engineers and contribute to technical standards and reusable frameworks

Basic Job Requirements

Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related discipline
Minimum 5 years of progressive experience in machine learning or applied data science roles
Strong proficiency in Python / R , ML libraries (scikit‑learn, TensorFlow, PyTorch, XGBoost, etc.)
Solid understanding of statistics, probability, and model evaluation techniques
Experience working with structured and unstructured data at scale
Proven ability to deploy ML models into production environments
Strong problem solving, communication, and stakeholder engagement skills
Bachelor’s degree required; Master’s degree preferred
Relevant certifications in ML, AI, or Cloud (Azure/AWS/GCP) are a plus

Master’s degree in Data Science, AI, or a related field
Experience in EPC, engineering, construction, manufacturing, or asset intensive industries
Exposure to time‑series forecasting, anomaly detection, or optimization models
Experience with cloud platforms (Azure preferred)
Familiarity with MLOps tools and practices
- Experience working in global, matrixed organizations