• Leading ML research, experimentation, and development from concept to deployment • Designing and implementing novel ML/AI approaches, staying current with cutting-edge research and methodologies • Architecting ML pipelines, training infrastructure, and model evaluation frameworks • Collaborating with cross-functional teams: Working closely with product managers, and other stakeholders to ensure the AI/ML solutions align with the organization's goals and objectives • Communicating effectively: Clearly document your work and effectively communicate your findings, insights, and recommendations to both technical and non-technical stakeholders, fostering a collaborative and informed environment • Guiding ML engineering decisions including model selection, feature engineering, and optimization strategies • Translating academic insights into practical applications • Mentoring junior ML engineers and establish ML best practices across the team • Working closely with AI Systems Tech Leads to ensure delivery of optimized AI systems and services to production • Enforcing data governance and privacy: Follow processes and implement methods that ensure data governance, privacy, and security

• Lead the strategy, design, and implementation of AI and machine learning solutions to support R&D digital transformation and operational efficiency. • Drive the adoption of AI across R&D by identifying high-impact use cases, building business cases, and partnering with scientific, statistical, clinical, and technology stakeholders. • Develop and deploy AI/ML models, tools, and platforms that improve the efficiency of digitalization systems, including clinical trial design, clinical data workflows, statistical analysis processes, document generation, knowledge management, and decision-support systems. • Evaluate emerging AI technologies, including generative AI, large language models, intelligent agents, automation frameworks, and advanced machine learning approaches, and assess their applicability in regulated pharmaceutical R&D environments.

Role Description Will work with other Automation and AI team members through the phases of use-case data exploration and prototyping to the design, implementation, and deployment of Cognitive services supporting use-cases. Specific responsibilities include: - Work with a team of data scientists, machine learning engineers, software engineers, and QA engineers. - Perform data collection and preprocessing with various tools and libraries like Apache Tika. - Build pipeline to integrate with other microservices to create workflow for solving business problems. - Engage with lines of business, users, and analysts to explore and prototype opportunities and use-cases exploiting data and the application of cognitive and machine learning technologies. - Design, develop, test, and support Cognitive microservices to operationalize and productize deployment of resulting models and cognitive solutions. - Manage a team of IT engineering performing AI and Cloud based development for use cases. - Supervise IT staff, assign tasks, and set priorities. - Conduct 1-1s with direct reports. - Foster collaboration and ensure skill development within the team. - Perform access reviews and recertifications for direct report access to various IT systems. - Conduct performance management functions and periodic reviews and performance ratings. Full time telecommuting from within the United States permitted pursuant to Company policy. Qualifications - Bachelor’s degree or its equivalent in Computer Science or related technical field; and 5 years of related work experience as a Software Engineer. - Alternatively, will accept a master’s degree or its equivalent in Computer Science, or a related technical field; plus 3 years of related work experience as a Software Engineer. Requirements - Demonstrated excellent programming skills and experience with Java. - Strong Database analysis and RDBMS programming skills. - Hands-on experience with SDLC, Agile methodologies, Cloud-DevOps. - Strong organizational, multitasking, analytical and time management skills. - Strong skills in Application design & Architecture including complex Integration, API development. Benefits - Retirement savings plan (401K) with company match. - Insurance coverage including basic life, medical, dental, vision, long-term disability, and other optional additional coverages. - Paid-time off including vacation, sick leave, short term disability, and family care responsibilities. - Access to our Employee Assistance Program. - Incentive compensation including eligibility for annual performance-based awards (excluding certain sales roles subject to sales incentive plans). - Eligibility for certain tax advantaged savings plans. Salary Range $178,131 - $180,000 Annual. The range quoted above applies to the role in the primary location specified. If the candidate would ultimately work outside of the primary location above, the applicable range could differ.

• Build end-to-end AI/ML/Agentic-AI solution — from ideation, research, and experimentation to deployment and monitoring in production • Manage project timelines, deliverables, and cross-team dependencies in coordination with product and engineering leads • Translate business and technical requirements into ML roadmap, architecture, and actionable workstreams • Drive adoption of MLOps best practices and champion operational excellence for ML infrastructure • Build and deploy models for cloud workload prediction, resource optimization, and intelligent automation • Integrate GenAI, LLM-based and Agentic AI solutions into customer-facing products and internal systems • Communicate ML strategy, progress, and insights effectively to both technical and non-technical stakeholders