Software Engineering Manager
Millipore Corporation

We are seeking a dynamic and experienced Software Engineering Manager to lead our talented team of engineers in the development and enhancement of our AI drug discovery platform (AIDDISON). As a Software Engineering Manager, you will play a critical role in shaping the technical direction, fostering a culture of innovation, and ensuring the successful delivery of high-quality software products.

Responsibilities:

Provide visionary technical leadership and mentorship to a dynamic team of software engineers, data scientists, and machine learning experts.Collaborate closely with cross-functional teams to translate business objectives into technical requirements and deliver innovative solutions that drive value.Direct the development and execution of project plans, ensuring alignment with strategic goals, timelines, and quality standards.Champion the adoption of best practices for software development, including MLOps methodologies for seamless integration, deployment, and monitoring of AI models.Stay at the forefront of generative AI research, evaluating emerging technologies and methodologies to enhance our AI drug discovery platform.Cultivate a culture of creativity, collaboration, and continuous learning within the engineering team, fostering an environment where bold ideas thrive. Qualifications:Bachelor's or Master's degree in Computer Science, Chemistry, Engineering or related field.At least 8 years' of experience in software development, with a focus on AI/ML and generative AI techniques.Proven track record of technical leadership and project management in a fast-paced, innovative environment.Expertise in programming languages such as Python, with hands-on experience in AI frameworks like TensorFlow, PyTorch, or GPT.Understanding of generative AI concepts, including generative adversarial networks (GANs), variational autoencoders (VAEs), and reinforcement learning.Familiarity with cloud computing platforms (e.g., AWS, Azure, GCP) and containerization/serverless technologies (e.g., Docker, Kubernetes).Strong understanding of MLOps principles and experience implementing MLOps pipelines for AI model deployment, monitoring, and optimization.Strong communication skills with the ability to convey complex technical concepts to diverse audiences.

Preferred Qualifications:

Knowledge of pharmaceutical regulatory requirements and compliances.In-depth understanding of small molecule drug discovery - design, make, test, analysis Location: This is a hybrid position, flexible to be located from either our St. Louis, MO or Burlington/Billerica, MA sites.