Design, implement, and deploy machine learning models for predictive analytics, recommendation systems, anomaly detection, and other AI-driven applications.
Work with large, complex datasets to perform data cleaning, feature engineering, and transformation for model training.
Develop end-to-end ML pipelines, from data ingestion to model deployment and monitoring in production.
Work with software engineers and product teams to integrate ML models into applications and services.
Monitor model performance, troubleshoot issues, and implement improvements to ensure reliability and accuracy.
Evaluate new algorithms, tools, and frameworks to enhance the company’s ML capabilities.
Document model architectures, assumptions, and design decisions for knowledge sharing and reproducibility.
Ideal Profile :
You possess an advanced degree, ideally a PHD, in Mathematics, Statistics, Computer Science or a related field.
7+ years of experience in machine learning, AI engineering, or applied data science.
Strong expertise in Python, ML frameworks (TensorFlow, PyTorch, scikit-learn), and data processing tools (Pandas, NumPy, Spark).
Hands-on experience designing and deploying ML models to production at scale.
Strong understanding of supervised, unsupervised, and reinforcement learning techniques.
Experience with cloud platforms (AWS, Azure, GCP) and deploying ML pipelines in cloud environments.
Ability to solve complex, ambiguous technical problems and deliver production-ready solutions.
Excellent collaboration and communication skills to work across engineering, data, and product teams.