Junior AI Engineer

Model Development and Deployment:

• Evaluate and select appropriate Generative AI models based on business needs, ensuring alignment with use case requirements.
• Leverage Azure ML, OpenAI APIs, and other Generative AI technologies based on a given design.
• Implement best practices for model development, training, and deployment pipelines.
• Create and deploy pipelines for model training, evaluation, and monitoring in Azure ML.Optimize model performance for latency, scalability, and accuracy, ensuring compliance with regulatory and organizational standards.

AI Integration and Innovation:

• Integrate Generative AI solutions with enterprise applications, APIs, and data sources.
• Leverage Azure AI model catalog (Microsoft, OpenAI, Mistral, Meta, etc) 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.

Collaboration and Leadership:

• Partner with cross-functional teams, including data engineers, cloud architects, and business analysts, to align AI/ML solutions with business objectives.
• Communicate complex (Gen) AI concepts to non-technical stakeholders, fostering a culture of innovation and understanding

Technical Skills:

• Experience Delivering GenAI (LLMs) solutions, preferably on Azure.
• Familiar with using Azure AI library APIs (e.g., GPT, Codex, DALLE) & other frameworks (e.g. Databricks Mosaic) to integrate Generative AI into business workflows.
• Proficient with at least one programming language, such as Python, PySpark, R, SQL, etc.
• Knowledge of big data technologies (e.g., Spark, Databricks), TensorFlow, PyTorch are a plus.
• Knowledge of Azure Cloud services (e.g., Azure AI Platform, Azure Data Factory, Azure Synapse, Azure Cognitive Services) and their integration with ML workflows is a plus.Knowledge of security best practices for AI solutions, including data encryption, access control, and endpoint protection is a plus.

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., * Experience with GenAI Large Language Models (LLMs) solution development and fine-tuning for domain-specific tasks.
• Certifications in Azure or Databricks (e.g., Azure AI Engineer Associate, Azure Solutions Architect Expert, Databricks ML Professional, Databricks Data Engineer Professional).
• Familiarity with AI ethics, bias mitigation, and explainability techniques.
• Prior experience in implementing AI/ML solutions in industries such as healthcare, finance, or retail is a plus.

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