Job Description

Summary
We are seeking a highly skilled and visionary Machine Learning Lead to lead the design, development, and deployment of cutting-edge AI/ML solutions using Azure Machine Learning, OpenAI APIs, and Generative AI technologies.
Key Responsibilities
Solution Design and Architecture:
Architect and design end-to-end AI/ML solutions leveraging Azure ML, OpenAI APIs, and other Generative AI technologies.
Develop scalable and secure architectures for AI solutions that integrate with existing enterprise systems and workflows.
Define and implement best practices for model development, training, and deployment pipelines.
Evaluate and select appropriate Generative AI models (e.g., GPT, DALLE) based on business needs, ensuring alignment with use case requirements.
Model Development and Deployment:
Collaborate with data scientists, engineers, and business stakeholders to design, develop, and fine-tune machine learning models.
Create and deploy pipelines for model training, evaluation, and monitoring in Azure ML.
Optimize model performance for latency, scalability, and accuracy, ensuring compliance with organizational standards.
AI Integration and Innovation:
Integrate Generative AI solutions with enterprise applications, APIs, and data sources.
Leverage OpenAI's APIs to implement conversational AI, document summarization, image generation, or other innovative use cases.
Explore advancements in AI/ML technologies, recommending tools, frameworks, and practices to enhance the organization's AI capabilities.
Governance and Compliance:
Establish governance frameworks to ensure ethical AI practices, data privacy, and regulatory compliance.
Implement monitoring and logging mechanisms for deployed ML solutions to ensure transparency and reliability.
Collaboration and Leadership:
Partner with cross-functional teams, including data engineers, cloud architects, and business analysts, to align AI/ML solutions with business objectives.
Mentor junior team members and provide technical guidance on best practices in AI/ML development and deployment.
Communicate complex AI concepts to non-technical stakeholders, fostering a culture of innovation and understanding.
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Technical Skills:
Expertise in designing and deploying machine learning solutions on Azure Machine Learning.
Strong experience with OpenAI APIs (e.g., GPT, Codex, DALLE) and integrating Generative AI into business workflows.
Proficiency in programming languages like Python and frameworks such as TensorFlow, PyTorch, and Scikit-learn.
Hands-on experience with MLOps practices, including CI/CD pipelines for ML, model versioning, and deployment automation.
Knowledge of Azure services (e.g., Azure Data Factory, Azure Synapse, Azure Cognitive Services) and their integration with ML workflows.
Architecture and Design:
Strong understanding of microservices architecture, API development, and cloud-native solution design.
Experience with big data technologies (e.g., Spark, Databricks) and their application in ML workflows.
Knowledge of security best practices for AI solutions, including data encryption, access control, and endpoint protection.
Soft Skills:
Excellent problem-solving and analytical thinking skills.
Strong communication and presentation skills, with the ability to translate technical concepts into business outcomes.
Proven ability to manage multiple stakeholders and prioritize tasks in a fast-paced environment
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Skills Required