Artificial Intelligence Consultant (5-8 yrs)

Job Summary :

We are seeking a highly dynamic and experienced AI/ML Engineer to join our growing team. This role will be pivotal in designing, developing, and deploying innovative AI/ML solutions, with a significant focus on Generative AI and Large Language Models (LLMs). The ideal candidate will possess deep technical expertise across a range of AI/ML frameworks and MLOps tools, coupled with strong communication and stakeholder engagement skills to effectively collaborate on customer-facing projects. If you are passionate about pushing the boundaries of AI, particularly in the realm of Generative AI, and thrive in a collaborative environment, we encourage you to apply.

Key Responsibilities :

- AI/ML Solution Design and Development : Design, develop, and implement end-to-end AI/ML solutions, with a strong emphasis on Generative AI applications leveraging LLMs.

- Generative AI and LLM Implementation : Lead and contribute to the implementation of Gen AI and LLM-based solutions, including but not limited to :

1. Developing and deploying applications utilizing Large Language Models.

2. Mastering Prompt Engineering techniques to optimize LLM outputs.

3. Executing Fine-tuning of pre-trained LLMs for specific use cases.

4. Architecting and implementing Retrieval-Augmented Generation (RAG) systems.

5. Integrating with OpenAI and Azure OpenAI services.

- Framework Proficiency : Demonstrate strong hands-on experience with key AI/ML frameworks such as TensorFlow, PyTorch, Scikit-learn, and Keras.

- MLOps Practices : Utilize and manage MLOps tools and platforms including MLFlow, AWS SageMaker, Google Vertex AI, and Azure ML for model development, training, deployment, and monitoring.

- Collaboration and Communication : Work closely with cross-functional teams, including product managers, data scientists, and software engineers, to understand business requirements and translate them into technical solutions.

- Customer Engagement : Effectively communicate complex AI/ML concepts and solutions to both technical and non-technical stakeholders, including clients. Strong storytelling skills are crucial for presenting findings and recommendations in a clear and compelling manner.

- Research and Innovation : Stay abreast of the latest advancements in AI/ML, particularly in Generative AI and LLMs, and proactively explore and propose innovative solutions to address business challenges and opportunities.

- Model Evaluation and Deployment : Develop and implement rigorous evaluation metrics for AI/ML models and manage the deployment process to ensure scalability, reliability, and performance.

Requirements :

Technical Expertise :

- Strong hands-on experience with core AI/ML frameworks : TensorFlow, PyTorch, Scikit-learn, and Keras.

- Deep understanding of Large Language Models (LLMs), including their architecture and capabilities.

- Proven experience in Prompt Engineering techniques for eliciting desired responses from LLMs.

- Hands-on experience with Fine-tuning pre-trained LLMs for specific tasks.

- Solid understanding and practical experience in implementing Retrieval-Augmented Generation (RAG) architectures.

- Experience integrating with OpenAI and/or Azure OpenAI services.

- Proficiency in utilizing ML Ops tools such as MLFlow, AWS SageMaker, Google Vertex AI, and Azure ML for the ML lifecycle.

Experience :

- Minimum of 5 years of professional experience in AI/ML solutioning and development.

- Demonstrated experience in the successful implementation of Generative AI and LLM-based solutions in real-world applications.

Communication and Interpersonal Skills : Exceptional communication (both written and verbal), stakeholder engagement, and storytelling skills are essential, particularly for effective interaction and presentations in customer-facing engagements.

Certifications : Any relevant OpenAI or Generative AI certifications will be considered a significant advantage.

Education : A Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related quantitative field is preferred.