Machine Learning + Python +Gen AI + Deep Learning

Machine Learning Lead / Principal ML Engineer

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Key Skills: Machine Learning • Python • Gen AI • Deep Learning

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Responsibilities

• Lead a team of 3–8 Machine Learning Engineers.
• Set and drive the strategic direction for AI/ML initiatives, identifying high-value opportunities aligned with company objectives.
• Architect, design, and oversee end-to-end development of scalable, production-grade ML systems delivering measurable business impact.
• Influence cross-functional teams and executive stakeholders, acting as a trusted technical advisor.
• Provide mentorship and technical leadership, guiding senior engineers and fostering a high-performance team culture.
• Evaluate and adapt cutting-edge research and open-source technologies into practical, deployable solutions.
• Establish technical standards for model development, evaluation, deployment, and monitoring, ensuring robustness, reproducibility, and ethical AI practices.
• Own the ML infrastructure and tooling roadmap to accelerate experimentation and deployment.
• Share thought leadership internally and externally through whitepapers, technical forums, and presentations.
• Prototype innovative ML applications and deliver PoCs to communicate strategic value.

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Requirements

• B.S., M.S., or Ph.D. in Computer Science, Engineering, or a related field.
• 10+ years of industry experience delivering ML solutions in production environments.
• Strong programming skills in Python, with experience in NumPy, pandas, matplotlib, and other core data science libraries.
• Deep expertise in ML frameworks including TensorFlow, PyTorch, and Scikit-Learn.
• Solid understanding of supervised and unsupervised learning, clustering, and forecasting.
• Strong foundation in statistical methods, with experience in classification, regression, and translating methods into scalable ML solutions.
• Proven experience designing robust, maintainable, and scalable codebases, mentoring engineers, and setting technical direction for ML projects.
• Track record of driving cross-functional initiatives and partnering effectively with product, data, and business teams.
• Excellent communication and collaboration skills.