AI / ML Engineer

Key Responsibilities

AI Solution Development & Deployment :

Design and implement AI models and algorithms using Azure AI services, including Azure Machine Learning, Cognitive Services, and Azure OpenAI.

Develop and deploy machine learning models, particularly focusing on NLP and LLMs, utilizing frameworks such as LangChain or Semantic Kernel.

Implement RAG architectures using Azure AI Search to enhance the performance and accuracy of generative AI applications.

Project Delivery & Client Engagement

Lead and contribute to the delivery of AI projects, ensuring solutions are scalable, secure, and aligned with client objectives.

Work in both project-based and staff augmentation roles, adapting to various client environments and requirements.

Provide technical expertise and guidance to clients, ensuring successful adoption and integration of AI solutions.

Model Validation & Quality Assurance

Conduct thorough testing and validation of AI models to ensure accuracy, reliability, and performance.

Optimize and fine-tune models, addressing issues related to data quality, bias, and fairness.

Stay current with industry trends and best practices in AI technology, incorporating them into solution development.

Preferred Consulting Experience

Collaborate with sales and delivery teams to design AI solutions that meet client needs.

Develop estimates and proposals for AI projects, articulating the value and feasibility of proposed solutions.

Conduct technical presentations and demonstrations to clients and stakeholders.

Education & Experience

Bachelor's Degree in Computer Science, Data Science or similar (relevant work experience is acceptable)

3+ years of experience in AI / ML development, with a focus on OpenAI Services, NLP and LLMs.

Experience in a consulting environment, engaging with clients and delivering tailored solutions.

Technical Skills

Proficiency in programming languages such as Python or C#.

Proficiency in Python and familiarity with ML frameworks such as PyTorch or TensorFlow.

Experience with Azure AI services, including Azure Machine Learning, Cognitive Services, and Azure OpenAI.

Familiarity with RAG architectures and tools like LangChain, Semantic Kernel, or LlamaIndex.

Model selection, validation, and workload optimization.

Knowledge of data processing and pipeline development using Azure Data Factory or similar tools.

Understanding of MLOps practices and tools for model lifecycle management.

Soft Skills

Strong analytical and problem-solving abilities.

Excellent communication and collaboration skills.

Ability to work independently and as part of a team in a dynamic, fast-paced environment.

Equal opportunity employer including disability / veterans.