Lead Machine Learning Engineer
3 weeks ago
Role Overview :
The Lead Machine Learning Engineer will spearhead the development and deployment of advanced machine learning models and solutions. This role involves designing and implementing ML algorithms, leading a team of engineers, and driving innovation in machine learning technologies.
Key Responsibilities :
- Model Development : Design, develop, and deploy machine learning models and algorithms to solve complex business problems. Ensure models are scalable, efficient, and effective.
- Team Leadership : Lead and mentor a team of machine learning engineers and data scientists. Provide guidance on best practices, code reviews, and technical challenges.
- Research and Innovation : Stay abreast of the latest advancements in machine learning and artificial intelligence. Drive innovation by integrating cutting-edge techniques and technologies into projects.
- Collaboration : Work closely with cross-functional teams, including data engineers, software developers, and product managers, to integrate machine learning solutions into applications and products.
- Data Management : Oversee the collection, processing, and management of data used for training and testing machine learning models. Ensure data quality and integrity.
- Performance Monitoring : Monitor the performance of machine learning models in production, identify issues, and implement improvements as necessary.
- Documentation : Maintain comprehensive documentation for ML models, processes, and methodologies. Ensure clear communication of technical concepts to non-technical stakeholders.
Skills and Qualifications :
- Experience : Minimum of 7 years of experience in machine learning, with a proven track record of developing and deploying complex models.
- Education : Master's or PhD in Computer Science, Data Science, Machine Learning, or a related field from a Tier 1 Institute.
- Technical Expertise : Strong proficiency in machine learning frameworks (e.g., TensorFlow, PyTorch), programming languages (e.g., Python, R), and data analysis tools.
- Leadership : Demonstrated experience leading and mentoring teams, with strong interpersonal and communication skills.
- Problem-Solving : Excellent analytical and problem-solving abilities, with a strong focus on innovation and optimization.
- Collaboration : Ability to work effectively in a remote environment and collaborate with diverse teams across different time zones.
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