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.
Qualifications
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
