Data Scientist/ AI Engineer

Data Scientist/ AI Engineer

Location: Hybrid - travel to Brighton and/or Burgess Hill 2-3 days a week

This role sits within our Intelligent Process Automation (IPA) practice. Customer preferences and demands can shift overnight. To stay ahead of fast-changing needs, business and IT leaders must partner together to accelerate and scale end-to-end business processes that think, learn and adapt on their own. Executives know that to thrive, modern businesses must transform to drive productivity and innovation. It requires moving beyond traditional automation to seize the opportunities presented by IPA.

What You'll Be Doing:

• Imagine new applications of generative AI to address business needs.
• Integrate Generative AI into existing applications and workflows.
• Collaborate with Machine Learning scientists and engineers to research, design and develop cutting-edge generative AI algorithms to address real-world challenges.
• Work across customer engagement to understand what adoption patterns for generative AI are working and rapidly share them across teams and leadership.
• Interact with customers directly to understand the business problem, help and aid them in implementation of generative AI solutions.
• Deliver briefing and deep dive sessions to customers and guide customer on adoption patterns and paths for generative AI.
• Create and deliver reusable technical assets that help to accelerate the adoption of generative AI on various platforms.
• Create and deliver best practice recommendations, tutorials, blog posts, sample code, and presentations adapted to technical, business, and executive stakeholders.
• Provide customer and market feedback to Product and Engineering teams to help define product direction.

What You'll Bring:

• Proficient in statistics, machine learning and deep learning concepts.
• Skilled in Python frameworks such as scikit-learn, scipy, numpy etc. and DL libraries such as TensorFlow, Keras.
• Skilled in GenAI Projects such as text summarization and chatbot creation using LLM models GPT4, Med-Palm, LLAMA etc.
• Skilled in fine-tuning open-source LLM models such as LLAMA2 and Google Gemma model to 1-bit LLM using LORA, Quantization, and QLORA techniques.
• Skilled in RAG-based Architecture using Langchain Framework & used Cohere model to fine-tune and re-rank the response of GenAI-based chatbots.
• Image classification using AI convolutional neural network models such as VGG16, ResNet, AlexNet, Darknet architectures in the Computer Vision domain.
• Object detection using various frameworks such as YOLO, TFOD, Detectron.
• Knowledge of image classification, object detection, tracking, and segmentation.
• Experience with Neural Networks, BERT, Transformers, RAG, Langchain, Prompt Engineering, Azure AI Search, Vector DB, Conversational AI, and LLMs such as Azure OpenAI (GPT4 turbo), LLAMA2, Google Gemma, and Cohere model.