
AI Model Developer
16 hours ago
Job Title
AI Model Development Engineer
About the Role
We are seeking a highly skilled AI Model Development Engineer to lead the development and deployment of advanced AI models.
This role emphasizes comprehensive technical skills and strategic oversight, including model fine-tuning, understanding and enhancing model architectures, and integrating cutting-edge research into robust, scalable production solutions.
You will oversee the deployment, monitoring, and continuous improvement of open-source and proprietary models for enterprise clients and internal products.
- Advanced Model Development & Optimization: Build, 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
To be successful in this role, you will need:
- Tech Skills: 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.
- 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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