AI/ML Solutions Architect
3 weeks ago
Key Responsibilities :
Technical Description and Responsibilities :
- Develop AI/ML Solutions : Design and implement machine learning algorithms and models for enterprise-level solutions on Azure/AWS cloud platforms.
- Communicate Effectively : Collaborate with clients to understand their needs and brainstorm solutions, ensuring effective communication of complex technical concepts.
- Research and Development : Conduct research and development on AI/ML implementations, focusing on state-of-the-art techniques and frameworks.
- Confidential Data Handling : Implement RAG architecture for the secure use of confidential data.
- Deep Learning Techniques : Apply deep learning techniques and leverage machine learning expertise to drive business outcomes.
- Model Optimization : Fine-tune large language models (LLMs) for optimal performance and develop generative AI models using cutting-edge techniques and frameworks.
Collaboration and Teamwork :
- Collaborate with cross-functional teams to understand project requirements and design solutions that address business needs.
- Stay updated with the latest advancements in AI research and technology, contributing to knowledge sharing within the team.
- Participate in code reviews, documentation, and knowledge transfer sessions to ensure high-quality deliverables and effective collaboration.
Qualifications :
- Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
- 3-5 years of experience in implementing ML/AI solutions for enterprise level on Azure/AWS cloud.
- Strong programming skills in languages such as Python, with experience in data science.
- Proficiency in generative AI techniques, including GANs (Generative Adversarial Networks), VAEs (Variational Autoencoders), and related architectures.
- Good understanding of machine learning concepts, algorithms, and methodologies.
- Experience with data preprocessing, model training, and evaluation using large-scale datasets.
- Excellent problem-solving skills and the ability to work independently as well as part of a team.
- Strong communication skills and the ability to convey complex technical concepts to non-technical stakeholders.
- Experience in healthcare and life sciences is a plus.
- Familiarity with MLOps, AIOps, and LLMOps is beneficial
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