Senior Solutions Engineer

Working with Us
Challenging. Meaningful. Life-changing. Those aren’t words that are usually associated with a job. But working at Bristol Myers Squibb is anything but usual. Here, uniquely interesting work happens every day, in every department. From optimizing a production line to the latest breakthroughs in cell therapy, this is work that transforms the lives of patients, and the careers of those who do it. You’ll get the chance to grow and thrive through opportunities uncommon in scale and scope, alongside high-achieving teams. Take your career farther than you thought possible.

Bristol Myers Squibb recognizes the importance of balance and flexibility in our work environment. We offer a wide variety of competitive benefits, services and programs that provide our employees with the resources to pursue their goals, both at work and in their personal lives. Read more: careers.bms.com/working-with-us.

Summary:

We are seeking a highly motivated and experienced Senior Solutions Engineer to partner with our Product Development (PD) organization in identifying and implementing impactful AI/ML solutions. This role is pivotal in transforming complex business challenges into data-driven insights and innovative AI and Machine Learning (AI/ML) applications. You will analyze PD workflows to uncover opportunities for AI-driven improvements, collaborate with cross-functional teams to integrate solutions seamlessly, and ensure alignment with regulatory requirements. Success in this role requires a strong understanding of the business needs, coupled with the technical acumen to guide the development and deployment of generative AI solutions

Responsibilities:

• Analyze business requirements and translate them into comprehensive, end-to-end ML/AI solution designs that leverage cloud-native technologies. This includes architecting and designing solutions primarily on AWS, with potential opportunities to work with GCP or Azure

• Evaluate and select appropriate large language models (LLMs) and frameworks (e.g., TensorFlow, PyTorch) based on a thorough analysis of business requirements and available data.

• Design the fine-tuning strategy, considering data preprocessing, hyperparameter optimization, and evaluation metrics, to ensure the LLM effectively addresses the specific needs of the application

• Analyze user and administrator needs to design intuitive and efficient self-service portals that democratize access to ML/AI capabilities within the organization. This includes gathering requirements, defining user workflows, and architecting a portal experience that empowers both technical and non-technical users to leverage ML/AI effectively

• Collaborate with product managers, data scientists, and other engineers to define project requirements and deliver high-quality solutions.

• Develop and maintain comprehensive documentation, including architecture diagrams, API specifications, and user guides.

• Act as a subject matter expert on AI/ML, providing guidance and mentorship to other team members.

• Contribute to the development of reusable components, libraries, and best practices for ML/AI development.

• Monitor and analyze the performance of ML/AI solutions, identifying areas for improvement and implementing optimizations.

• Stay up-to-date with the latest advancements in generative AI research and technology, and evaluate their potential application to our business.

• Participate in code reviews and contribute to the improvement of our software development processes.

Required Skills:

• 5+ years of experience as a Senior Software Engineer with a focus on AI and machine learning.

• 3+ years of hands-on experience building and deploying generative AI solutions using large language models (LLMs), diffusion models, or other generative techniques.

• Deep understanding of LLM architectures, training methodologies, and fine-tuning techniques.

• Proven experience in prompt engineering, including the ability to design effective prompts for various tasks.

• Strong programming skills in Python and experience with relevant libraries such as TensorFlow, PyTorch, Transformers, etc.

• Experience with cloud platforms such as AWS (preferred), Azure, or Google Cloud.

• Proficiency with DevOps principles and tools, including CI/CD pipelines and infrastructure-as-code (IaC) practices.

• Experience with API design and development (REST, GraphQL).

• Strong understanding of data engineering