
Senior AI/ML Architect
2 days ago
We are seeking a seasoned AI/ML professional to lead the development and deployment of cutting-edge artificial intelligence and machine learning models. This role emphasizes comprehensive technical expertise and strategic oversight, including model optimization, architecture enhancement, and integration of advanced research into robust production solutions.
About the Role
This is an exceptional opportunity for a highly skilled technologist to drive innovation and deliver tangible business outcomes through data-driven insights.
Key Responsibilities- Advanced Model Development & Optimization: Develop, fine-tune, and optimize traditional machine learning and deep learning models to deliver scalable, production-grade solutions across multiple domains (NLP, Vision, Audio).
- Research & Technical Leadership: Stay current with state-of-the-art machine learning and deep learning research, translating complex theoretical knowledge into practical, impactful business applications.
- Strategic Deployment & Monitoring: Lead the development of sophisticated deployment strategies and robust monitoring frameworks, ensuring continuous performance evaluation and iterative improvement.
- Cross-Functional Collaboration: Partner closely with data engineers, AI solutions engineers, software developers, and business leaders to align technical decisions with strategic business outcomes.
- Technical Mentorship: Guide junior engineers and promote high engineering standards, best practices, and continuous learning within the team.
- Comprehensive Documentation & Communication: Clearly document and communicate complex technical solutions, methodologies, and results to stakeholders across the organization.
Requirements
- Technical Skills:
- Educational Background: Background in Computer Science, Data Science, Statistics, Mathematics, or a related technical discipline.
- Technical Mastery: 4+ years of hands-on experience developing, deploying, and optimizing machine learning and deep learning models. Proficient in Python and libraries/frameworks such as TensorFlow, PyTorch, scikit-learn, and familiarity with cloud platforms like AWS, Azure, or GCP.
- Strong Data Science Fundamentals: Deep understanding of traditional machine learning techniques, statistical analysis, predictive modeling, and advanced data science concepts.
- Deep Learning Expertise: Proven ability to implement and fine-tune complex neural network architectures, including transformer-based models, CNNs, and RNNs. Production expertise highly desirable.
- Strategic Problem-Solving: Demonstrated ability to address ambiguous problems strategically, creatively, and analytically, driving measurable business outcomes.
- Excellent Communication Skills: Ability to clearly articulate technical solutions and insights to diverse stakeholders, from engineers to executives.
- Proven Track Record: Experience delivering AI-driven solutions to production, demonstrating tangible impact and continuous improvement through data-driven insights.
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