1 Talent2suit Job
Data Engineer - Machine Learning Models (6-8 yrs)
Talent2suit
posted 1mon ago
Key skills for the job
Role Overview :
The AI/ML Lead / Architect will drive the strategic direction and architecture of AI/ML initiatives within the organization. This role requires deep expertise in AI/ML concepts and significant experience in deploying scalable solutions on AWS and GCP. The AI/ML Lead / Architect will play a key role in guiding the technical team, ensuring the robustness of AI/ML systems, and aligning AI/ML strategies with business goals.
Key Responsibilities :
- Lead the design, development, and deployment of advanced machine learning models and algorithms.
- Architect end-to-end AI/ML solutions that are scalable, efficient, and aligned with business objectives.
- Collaborate closely with data scientists, software engineers, and other stakeholders to integrate AI/ML solutions into products and services.
- Stay at the forefront of AI/ML research and technology trends to ensure best practices and innovative solutions are adopted.
- Provide technical leadership, guidance, and mentorship to the AI/ML engineering team.
- Oversee the optimization and scaling of ML models to ensure performance, efficiency, and reliability.
- Ensure that AI/ML systems are secure, robust, and compliant with industry standards.
Qualifications :
- Bachelor's or Master's degree in Computer Science, Data Science, or a related field.
- 6+ years of relevant experience in machine learning, AI, and related fields, with a proven track record of leading AI/ML projects.
- Extensive experience with AWS and GCP cloud services, including architecture design and deployment.
- Advanced programming skills in Python or similar languages, with deep experience in ML frameworks like TensorFlow, PyTorch, or similar.
- Strong leadership skills with the ability to lead and inspire a technical team.
- Experience in a dynamic and diverse work environment, understanding intercultural aspects.
- Excellent communication and collaboration skills to work effectively with cross-functional teams and stakeholders.
Functional Areas: Software/Testing/Networking
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