01Key Responsibilities
- Lead a team of 3 to 8 Machine Learning Engineers- Set and drive the strategic direction for AI/ML initiatives- Architect, design, and oversee end-to-end development of scalable, production-grade ML systems- Influence cross-functional teams and executive stakeholders- Provide mentorship and technical leadership- Evaluate and adapt cutting-edge research and open-source technologies- Establish technical standards for model development, evaluation, deployment, and monitoring- Own the ML infrastructure and tooling roadmap- Share thought leadership internally and externally- Prototype innovative ML applications and deliver PoCs
02Qualifications Required
- 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- Solid 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- Solid 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 As a Machine Learning Engineering Lead, you will be responsible for leading a team of 3 to 8 Machine Learning Engineers. Your role will involve setting and driving the strategic direction for AI/ML initiatives that are aligned with the companys objectives. You will architect, design, and oversee the end-to-end development of scalable, production-grade ML systems that deliver measurable business impact. Additionally, you will influence cross-functional teams and executive stakeholders, acting as a trusted technical advisor. Your responsibilities will also include providing mentorship and technical leadership, guiding senior engineers, and fostering a high-performance team culture. You will evaluate and adapt cutting-edge research and open-source technologies into practical, deployable solutions. Furthermore, you will establish technical standards for model development, evaluation, deployment, and monitoring to ensure robustness, reproducibility, and ethical AI practices. You will own the ML infrastructure and tooling roadmap to accelerate experimentation and deployment. Sharing thought leadership internally and externally through whitepapers, technical forums, and presentations will also be part of your role. Finally, you will prototype innovative ML applications and deliver PoCs to communicate strategic value.
03Key Responsibilities
- Lead a team of 3 to 8 Machine Learning Engineers- Set and drive the strategic direction for AI/ML initiatives- Architect, design, and oversee end-to-end development of scalable, production-grade ML systems- Influence cross-functional teams and executive stakeholders- Provide mentorship and technical leadership- Evaluate and adapt cutting-edge research and open-source technologies- Establish technical standards for model development, evaluation, deployment, and monitoring- Own the ML infrastructure and tooling roadmap- Share thought leadership internally and externally- Prototype innovative ML applications and deliver PoCs
