Sr. Engineer - Artificial Intelligence

We are seeking a highly skilled Sr. Engineer - Artificial Intelligence to join our team. This role is crucial for designing, developing, and deploying AI models and data-driven solutions for real-world projects. You will play a pivotal part in helping businesses make informed decisions by collaborating with stakeholders, creating algorithms, and providing meaningful insights. The ideal candidate will have extensive experience in machine learning, with a specific focus on generative AI models and their integration into production environments.

Key Responsibilities

• AI Solution Development: Design, train, fine-tune, and evaluate generative AI models such as GPT, LLaMA, Stable Diffusion, and DALL-E.
• Model Integration: Integrate foundational models and Retrieval-Augmented Generation (RAG) techniques to enhance model capabilities.
• Full-Stack Implementation: Implement backend services and API endpoints to support AI solutions, and develop or adapt frontend interfaces for user interaction.
• Optimization: Optimize models for performance, latency, and cost within production environments.
• Collaboration & Mentorship: Work with cross-functional teams (product, research, engineering) to integrate GenAI capabilities. Mentor junior engineers and contribute to best practices.
• Ethical AI: Ensure ethical and responsible AI practices are followed in model design and usage.

Qualifications

• A Bachelor's or Master's degree in Computer Science, Machine Learning, Mathematics/Statistics, or a related field.
• Proven experience in machine learning, with a strong focus on generative AI.
• Experience with GenAI use cases in the Chemical, Pharma, or Manufacturing industries is a plus.
• A highly agile individual with a drive to make a global impact.

Skills

• Technical Proficiency: Deep proficiency in Python for data handling and AI scripting.
• Generative AI Expertise: Strong knowledge of prompt engineering techniques and familiarity with foundational generative AI models and Natural Language Processing (NLP).
• Data Engineering: Experience with data pipeline development, ETL processes, and data preprocessing.
• Modeling: Expertise in predictive modeling, including traditional supervised and unsupervised learning.
• Software Development: Knowledge of testing frameworks and automated testing for QA processes.
• Collaboration: Excellent communication and collaboration skills to work with cross-functional teams.