AI/ML Engineer Azure & GPT Development
Job Title: AI/ML Engineer Azure & GPT Development
Location: Atlanta, GA (Hybrid 3 Days Onsite)
Engagement: Contract Position
Duration: Long term
Compensation: Competitive, based on experience
Position Overview:
We are seeking a highly skilled and motivated AI/ML Engineer with proven experience in building Large Language Models (LLMs) from scratch on the Azure platform. In this role, you will leverage Microsoft Azure s comprehensive suite of cloud services to design, build, and deploy sophisticated AI models that power GPT-based solutions for internal customer-facing applications. Your expertise in prompt engineering, retrieval augmented generation (RAG), and advanced machine learning frameworks will be key to driving innovative and impactful solutions.
Key Responsibilities:
AI Model Development:
- Build and train custom LLMs from scratch utilizing Azure services.
- Develop robust architectures to meet specific business requirements.
GPT & Prompt Engineering:
- Design and optimize prompts for GPT models to deliver accurate and high-quality responses.
- Incorporate prompt engineering best practices to improve model output.
Azure Cloud Services:
- Utilize Azure Machine Learning, Azure Cognitive Services, Azure Open AI, and other related services for model deployment and management.
- Integrate GPT Services and other Azure AI offerings into scalable solutions.
Advanced ML Techniques:
- Implement Retrieval Augmented Generation (RAG) strategies to enhance model performance.
- Work with vector embeddings and FAISS to enable efficient similarity searches and data retrieval.
Model Optimization & Feedback:
- Set up and manage feedback loops to continuously refine and improve model performance.
- Utilize frameworks such as TensorFlow, PyTorch, and Keras to build and fine-tune AI/ML models.
Collaboration & Documentation:
- Work closely with data engineering, product management, and business teams to integrate diverse data sources and deliver actionable insights.
- Maintain comprehensive documentation of model architectures, training processes, and prompt designs.
Continuous Learning:
- Stay up-to-date with the latest advancements in AI/ML and Azure cloud technologies, and apply new methodologies to enhance our solutions.
Required Skills & Experience:
- Proven Experience:
- Demonstrable track record of building an LLM from scratch on Azure.
- Azure Expertise:
- Hands-on experience with Azure Services including Azure ML, Azure AI, Azure Open AI, and GPT Services.
- GPT & Prompt Engineering:
- Experience in developing and fine-tuning GPT models along with strong prompt engineering skills.
- Advanced Machine Learning Techniques:
- Familiarity with Retrieval Augmented Generation (RAG) techniques.
- Experience with vector embeddings and FAISS.
- ML Frameworks:
- Proficiency in one or more of TensorFlow, PyTorch, or Keras.
- Feedback Loop Implementation:
- Ability to design and implement effective feedback loops to optimize model performance.
- Programming & Data Skills:
- Strong programming skills in Python and familiarity with relevant ML libraries.
Preferred Qualifications:
- Azure certifications (e.g., Microsoft Certified: Azure AI Engineer Associate) are a plus.
- Experience in building GPT or similar AI solutions for customer-facing applications.
- Excellent communication skills with the ability to articulate technical concepts to non-technical stakeholders.
Job Title: AI/ML Engineer Azure & GPT Development
Location: Atlanta, GA (Hybrid 3 Days Onsite)
Engagement: Contract Position
Duration: Long term
Compensation: Competitive, based on experience
Position Overview:
We are seeking a highly skilled and motivated AI/ML Engineer with proven experience in building Large Language Models (LLMs) from scratch on the Azure platform. In this role, you will leverage Microsoft Azure s comprehensive suite of cloud services to design, build, and deploy sophisticated AI models that power GPT-based solutions for internal customer-facing applications. Your expertise in prompt engineering, retrieval augmented generation (RAG), and advanced machine learning frameworks will be key to driving innovative and impactful solutions.
Key Responsibilities:
AI Model Development:
- Build and train custom LLMs from scratch utilizing Azure services.
- Develop robust architectures to meet specific business requirements.
GPT & Prompt Engineering:
- Design and optimize prompts for GPT models to deliver accurate and high-quality responses.
- Incorporate prompt engineering best practices to improve model output.
Azure Cloud Services:
- Utilize Azure Machine Learning, Azure Cognitive Services, Azure Open AI, and other related services for model deployment and management.
- Integrate GPT Services and other Azure AI offerings into scalable solutions.
Advanced ML Techniques:
- Implement Retrieval Augmented Generation (RAG) strategies to enhance model performance.
- Work with vector embeddings and FAISS to enable efficient similarity searches and data retrieval.
Model Optimization & Feedback:
- Set up and manage feedback loops to continuously refine and improve model performance.
- Utilize frameworks such as TensorFlow, PyTorch, and Keras to build and fine-tune AI/ML models.
Collaboration & Documentation:
- Work closely with data engineering, product management, and business teams to integrate diverse data sources and deliver actionable insights.
- Maintain comprehensive documentation of model architectures, training processes, and prompt designs.
Continuous Learning:
- Stay up-to-date with the latest advancements in AI/ML and Azure cloud technologies, and apply new methodologies to enhance our solutions.
Required Skills & Experience:
- Proven Experience:
- Demonstrable track record of building an LLM from scratch on Azure.
- Azure Expertise:
- Hands-on experience with Azure Services including Azure ML, Azure AI, Azure Open AI, and GPT Services.
- GPT & Prompt Engineering:
- Experience in developing and fine-tuning GPT models along with strong prompt engineering skills.
- Advanced Machine Learning Techniques:
- Familiarity with Retrieval Augmented Generation (RAG) techniques.
- Experience with vector embeddings and FAISS.
- ML Frameworks:
- Proficiency in one or more of TensorFlow, PyTorch, or Keras.
- Feedback Loop Implementation:
- Ability to design and implement effective feedback loops to optimize model performance.
- Programming & Data Skills:
- Strong programming skills in Python and familiarity with relevant ML libraries.
Preferred Qualifications:
- Azure certifications (e.g., Microsoft Certified: Azure AI Engineer Associate) are a plus.
- Experience in building GPT or similar AI solutions for customer-facing applications.
- Excellent communication skills with the ability to articulate technical concepts to non-technical stakeholders.