JOB DATA

JOB TITLE: Senior Technical Consultant- Azure AI 

Key Responsibilities

1. Design and Implement AI Solutions

• Architect, develop, and deploy AI/ML solutions using Azure services (e.g., Azure Machine Learning, Azure Cognitive Services, Azure OpenAI Service, Azure Databricks).
• Integrate cutting-edge generative AI models (LLMs, text-to-image, etc.) into production workflows, ensuring scalability, reliability, and security.

1. Generative AI Model Development

• Develop and fine-tune generative AI models (e.g., GPT, DALL·E, Stable Diffusion) to meet specific business requirements.
• Collaborate with data scientists to transform proof-of-concept generative solutions into production-grade offerings.
• Continuously monitor generative AI trends and best practices to keep the organization at the forefront of innovation.

1. MLOps and Deployment

• Automate end-to-end ML pipelines—training, testing, deployment, monitoring—using Azure DevOps, CI/CD best practices, and containerization (Docker, Kubernetes).
• Establish model governance frameworks to manage versioning, model drift, and data compliance.

1. Data Management

• Work with data engineers to build and optimize data pipelines for training, inference, and continuous model learning.
• Ensure data quality, integrity, and security throughout the AI development lifecycle.

1. Performance Optimization

• Fine-tune ML and generative models for resource efficiency and optimal performance on Azure.
• Proactively troubleshoot performance bottlenecks and implement corrective measures.

1. Collaboration and Communication

• Collaborate cross-functionally (software engineering, product, design, etc.) to align AI solutions with business goals.
• Document and communicate technical designs, roadmaps, and updates to both technical and non-technical stakeholders.

1. Research and Innovation

• Stay current on emerging AI/ML and Generative AI trends, frameworks, and tools, recommending advancements that can enhance our AI initiatives.
• Champion a culture of continuous learning and experimentation across the organization.

Qualifications

• Education:
• Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, or a related field (or equivalent experience).
• Experience:
• 3+ years of hands-on AI/ML engineering experience, with a strong focus on Microsoft Azure.
• Proven experience with Generative AI models (LLMs, text or image generation) is highly desirable.
• Technical Skills:
• Proficiency in Python (preferred) or R.
• Hands-on experience with key Azure services (Azure Machine Learning, Azure OpenAI Service, Azure Cognitive Services, Azure Databricks, Azure Data Factory).
• Familiarity with containerization (Docker, Kubernetes) and CI/CD pipelines (Azure DevOps).
• Strong understanding of machine learning algorithms, model optimization, MLOps, and generative model training/fine-tuning.
• Knowledge of big data technologies like Spark is a plus.
• Experience with popular generative AI frameworks (e.g., Hugging Face Transformers, PyTorch, TensorFlow) is advantageous.
• Soft Skills:
• Excellent problem-solving and analytical abilities.
• Strong communication and collaboration skills.
• Ability to work in a fast-paced, agile environment, managing multiple priorities effectively.

Preferred Qualifications

• Relevant Azure certifications (Azure AI Engineer Associate, Azure Solutions Architect, etc.).
• Demonstrated experience with large-scale model deployment (LLMs, image generation, multimodal models).
• Familiarity with prompt engineering and fine-tuning techniques for generative models.
• Experience with Agile/Scrum methodologies.
• Proficiency with data visualization and business intelligence tools (Power BI, Tableau).