Senior Specialist, AI Engineering (Hybrid)

Merck KGaA Darmstadt Germany - Rahway, NJ

Full-time - Mid Level

Rahway, NJ

Chemical Manufacturing

About the position

As a Senior Specialist in AI Engineering at Merck, you will play a pivotal role in transforming the way our company leverages Artificial Intelligence to enhance pharmaceutical advancements. This position is situated within the Chief Technology Office, reporting directly to the Director of Intelligence Automation & Hyperautomation. Your primary responsibility will be to integrate AI models into production systems, ensuring their seamless operation across the organization. This is an exciting opportunity for a driven individual who is passionate about pioneering innovative solutions that can significantly impact people's lives. In this role, you will be tasked with writing efficient and maintainable code while adhering to best practices in software engineering. You will utilize DevSecOps tools for deploying and versioning code, and conduct thorough research and analysis of various retrieval techniques, language models, and generative AI methodologies. Collaboration will be key, as you will work closely with data engineers to ensure the efficiency and accuracy of data pipelines, continuously iterating and refining retrieval augmented generation (RAG) methods based on experimentation and feedback. Your responsibilities will also include experimenting with different retrieval strategies to augment generative AI models, optimizing and fine-tuning AI models for performance, scalability, and accuracy. You will engage with cross-functional teams, including product managers, data scientists, and software engineers, to understand requirements and deliver AI-driven solutions. Presenting findings and insights to stakeholders will be crucial, as will documenting AI models, algorithms, and processes thoroughly. Staying updated with the latest advancements in AI and machine learning technologies will be essential to your success in this role. Additionally, you will participate in Agile ceremonies to execute prioritized projects and features, and implement automated testing and monitoring techniques to ensure the reliability of AI systems.

Responsibilities

• Write efficient and maintainable code following best practices in software engineering.
• Work with DevSecOps tools for deploying and versioning code.
• Conduct thorough research and analysis of retrieval techniques, language models, and generative AI methodologies.
• Collaborate with data engineers to ensure data pipeline efficiency and accuracy.
• Continuously iterate and refine retrieval augmented generation (RAG) methods and processes based on experimentation, analysis, and feedback.
• Experiment with different retrieval strategies to augment generative AI models.
• Optimize and fine-tune AI models for performance, scalability, and accuracy.
• Work closely with cross-functional teams to understand requirements and deliver AI-driven solutions.
• Present findings and insights to stakeholders and contribute to strategic decision-making.
• Document AI models, algorithms, and processes thoroughly.
• Prepare technical reports and presentations to communicate results and methodologies.
• Stay up to date with the latest advancements in AI and machine learning technologies.
• Participate in Agile ceremonies with the team to execute on prioritized projects and features.
• Implement automated testing and monitoring techniques to ensure the accuracy and reliability of AI systems.

Requirements

• Bachelor's in Engineering, Science, Mathematics or Information/Computer related field.
• 5 years of experience in AI Engineering.
• Strong programming skills in Python.
• Experienced in building scalable AI Solutions within a modern technology stack including cloud services, data pipelines, and databases.
• Experienced with CI/CD and test-driven development.
• Experience in building Restful APIs for AI models.
• Experience in designing scalable AI Solutions.
• Solid understanding of machine learning concepts (i.e. neural networks, optimization algorithms, evaluation metrics).
• Familiar with Retrieval Augmented Generation (RAG) techniques.
• Familiarity with prompt engineering techniques, such as instruction design, template-based approaches, rule-based conditioning, or fine-tuning strategies.
• Excellent communication and collaboration skills.
• Analytical, detail-oriented, and able to manage multiple projects simultaneously.

Nice-to-haves

• Experience working in an Agile Methodology.
• Additional programming languages such as Node.js / TypeScript, C#, or Java.
• Demonstrated experience in developing and refining prompts for generative AI models, preferably in creative or text generation domains.
• Experience with AWS Cloud.
• Experience with building, deploying, and managing docker images.