Lead AI Engineer

3 weeks ago


Olympia, United States Tech Mahindra Full time

Senior Azure AI/ML Practitioner: ·

Credential Required :

Certifications in AZ104, AI102, and AZ305. ·

Experience Requirement:

6-10 years at the helm of AI projects, with a strong emphasis on Generative AI and Azure Infra/App Services. ·

Core Proficiencies:

Deep-seated expertise in Azure cloud infrastructure, Azure AI, and machine learning capabilities, thorough mastery in an array of Generative AI models, including but not limited to GPT series and Whisper, with the capacity to direct the progression and scaling of complex AI solutions. A firm foundation in and practical application of Azure Cognitive Services is indispensable.

Essential Expertise Needed:

1.

Generative AI:

A profound understanding of Generative AI concepts, including extensive knowledge of the GPT series (GPT-3, GPT-3.5, GPT-4), Whisper, and the latest embedding technologies. 2.

Azure Mastery:

Strong experience with the Azure ecosystem, specifically with AI and machine learning services, and the capacity to leverage these for innovative AI solution development. 3.

Model Training & Analytics:

Skilled in the nuanced training, optimization, and evaluation of AI models, with a particular focus on generative and predictive models. 4.

Data Engineering Excellence:

Capabilities in sophisticated data collection, cleansing, and ensuring data integrity for the training of advanced AI systems. 5.

Ethical AI Implementation:

Comprehension of ethical considerations in AI, such as bias prevention, ethical data usage, and compliance with regulatory standards. 6.

Cloud Computing Proficiency:

Expertise in cloud services and platforms that support AI development, deployment, and operation. 7.

Lifecycle Management:

Aptitude for managing the entire lifecycle of AI development projects, from initial data setup through to deployment and maintenance. 8.

Data Processing Acumen:

Exceptional skills in data processing, including cleaning, normalization, augmentation, feature engineering, and extraction. 9.

Innovation and R&D:

Encouragement of innovative thinking and research and development activities to stay at the forefront of AI advancements. 10. Product Development Savvy:

Experience in guiding AI projects from conception to market-ready products, with a focus on ensuring scalability and system robustness.

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