Job Summary:

Combine expertise in machine learning and data science to develop, validate, and deploy production-grade models. You will transform complex data into actionable insights and scalable solutions for agentic AI systems.

Key Responsibilities:

• Develop and deploy machine learning models that address business challenges and improve system performance.
• Conduct data wrangling, exploratory analysis, and feature engineering on large datasets.
• Collaborate with cross-functional teams to integrate ML models into production systems.
• Monitor model performance, retrain models as needed, and optimize pipelines for efficiency.
• Translate business requirements into technical solutions and actionable insights.
• Communicate findings and technical insights to non-technical stakeholders through clear visualizations and reports.
• Stay updated on the latest research and trends in AI/ML to drive innovation.

Qualifications:

• Master’s or Ph.D. in Computer Science, Statistics, Mathematics, or a related quantitative field.
• 5–10 years of experience in ML engineering, data science, or a combined role.
• Proficiency in Python and ML frameworks (TensorFlow, PyTorch, scikit-learn).
• Strong background in statistical analysis, predictive modeling, and data visualization.
• Experience with big data technologies and distributed computing frameworks (e.g., Spark).
• Excellent analytical, problem-solving, and communication skills.
• Proven ability to manage end-to-end projects from concept to production deployment.