Associate Director, AI Engineer

1 week ago

Mississauga, Ontario, Canada AstraZeneca Full time

Description

Company

AstraZeneca is a global, innovation-driven biopharmaceutical business that focuses on the discovery, development and commercialization of prescription medicines for some of the world's most serious diseases. But we're more than one of the world's leading pharmaceutical companies. At AstraZeneca, we're proud to have a unique workplace culture that inspires innovation and collaboration. Here, employees are empowered to express diverse perspectives and are made to feel valued, energized and rewarded for their ideas and creativity.

Department – Clinical Data & Insights

The Clinical Data & Insights Team is a global team of highly experienced and skilled professionals passionate about delivering state of the art services and solutions within R&D. AI has the potential to transform every step of the R&D pipeline. Through recent advancements in technology, we are now collecting a large amount of data, and have the opportunity to harness that data for analytics and insight that will help deliver a new generation of medicines that are capable of addressing the world's most challenging unmet medical needs. The mission of our team is to transform the way R&D uses data, analytics and AI to streamline processes and mitigate risks while building operational efficiencies. To achieve this, we partner with business functions within R&D to deliver cutting-edge capabilities and solutions that enable them to accelerate medicines that are safe and effective for patients.

Role

The Associate Director, AI Engineer will focus on applying state of the art AI approaches to AstraZeneca's data to derive new insights, unlock predictive power, and automate expensive cognitive processes. This is accomplished by training models to encode sophisticated data. In this role, you'll own the technical delivery and implementation of Generative AI capabilities within BioPharma Clinical Operations. You will work closely with a community of data experts driving team cohesion, engagement, morale and sharing of best practices. Competitive candidates will have a proven track record of delivering AI applications bringing excellent technical oversight and development of the best coding and engineering practices for the team.

Technical Leadership:

Provide technical leadership in the aspects of machine learning and AI solution engineering. Collaborate with cross-functional teams to define and execute the product roadmap. Stay updated on the latest developments in AI and related technologies to ensure our platform remains at the forefront of the industry. Drive research efforts to explore new machine learning and AI techniques that can enhance our product offerings. Identify opportunities for innovation and differentiation in the clinical trial optimization space. Advocate and advance modern, agile development practices and help develop and evangelize a great engineering culture

Team Management:

Coach and mentor team members in a matrix organization. Lead, inspire and be a key part of team development and retention. Foster a culture of innovation, collaboration, and continuous learning within the team. Set clear goals, supervise progress, and provide regular feedback to team members.

Quality, Security and Compliance:

Implement and enforce security protocols and best practices to protect sensitive data. Ensure compliance with data privacy regulations and industry standards (, GDPR (General Data Protection Regulation), HIPAA (Health Insurance Portability and Accountability). Collaborate with security teams to conduct regular vulnerability assessments and audits. Implement rigorous testing and quality assurance processes to maintain high product quality.

Documentation and Training:

Be a champion for high standards to ensure best practices are developed in the team. Create and maintain documentation related to platform configuration, processes, and best practices. Provide training and support to development teams on platform usage and optimization.

Candidate Knowledge, Skills and Experience

Bachelor's Degree from an accredited college or university with a major in Computer Science, Information Systems, Engineering, Mathematics, or equivalent experience in a related scientific or technical discipline. Proven experience in managing AI/ML development platforms. Strong understanding of machine learning and artificial intelligence concepts. Strong software development skills and proficiency in Python. Experience with one or more DL frameworks such as Tensorflow or PyTorch. Experience with scientific and machine learning libraries , SciPy, Scikit-learn, NumPy. Exposure to Knowledge Graph/graph technologies Ability to explain and present analyses and machine learning concepts to a broad audience. Ability to work with loosely defined objectives and turning these into concrete machine learning problems. Knowledge of containerization technologies (, Docker, Kubernetes). Knowledge of cloud platforms (, AWS, Azure, GCP) and modern DevOps practices. Proficiency in security best practices, data protection, and encryption methods. Experience with leading database technologies and data query languages. Strong project management and time management skills. Excellent communication and interpersonal abilities to engage with customers and internal stakeholders. Experience in software engineering and machine learning best practices, including version control, continuous integration (CI) and continuous development (CD), containerization, and shell scripting. Creative, collaborative, & product focused.

Date Posted

05-Jun-2024

Closing Date

04-Jul-2024

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