Job Description

Job Title: Associate Director - AI Engineering Lead

Career level - F

Introduction to role:

We are seeking a seasoned data and AI professional to own and drive the R&D AI team in our Global Technology Centre, Chennai. This role will directly support the delivery of AstraZeneca\xe2\x80\x99s ambition of putting AI at the heart of 80% of our business processes by 2025. You will be accountable and support RD business in implementing AI solutions leveraging the AI Engineering and ML Ops teams in GITC locations, develop new frameworks for how we use AI across RDIT. The AI lead will work collaboratively across R&D IT Data & AI leads at Hub locations to develop and execute the R&D IT2025 strategy, to help achieve our R&D IT goals, Leads AI with Insights.

This is a fantastic opportunity to join the R&D IT Data & AI team, We are looking for someone with the relevant experience to lead and deliver AI projects responsibly and ethically. Driving the introduction, evaluation and implementation of new AI frameworks and tooling, will require you to balance technical skills with program management and driving team objectively, in dynamic environment.

The ideal candidate will have industry experience in leading different types of artificial intelligence teams including machine learning, implementing data processing pipelines, but also managing enterprise IT systems and projects.

The position will work closely with R&D IT AI leads across sites, enhancing and introducing new technologies like Generative AI and tools to make R&D IT successful with AI at enterprise scale. You will work as part of a global team of deeply technical AI leads, data scientists, knowledge graph engineers & machine learning engineers and have the chance to work with technologies that will advance the standard of healthcare improving the lives of millions of patients across the globe.

Accountabilities:
Key Accountabilities

• Lead the AI team in Chennai, across ML Ops, Deep learning, Graph and Generative AI in delivering to the projects across the R&D portfolio.
• Strong Technical leader, identifying opportunities to apply AI, ML / DL and Generative AI tools and build quick solutions (MVP), which can be improved to Enterprise grade on approval.
• Define engineering practices and standards, policies (including AI Ethics), and methodology to ensure data privacy and GxP compliances are handled appropriately.
• Build tools, frameworks and enterprise assets which can be cross leveraged, across the RD Data & AI Platforms to deliver business agility, reuse, and optimization.
• Evaluate latest tools, tech stack, validate for enterprise alignment, and drive architecture discussion and decisions.
• Being responsible to deliver the Architecture blueprint, present to Ent Architecture / review board for approval, and follow through for adoption in design standards.
• Collaborate with Data Scientists, Data Engineers, ML Engineers, cloud platform and application engineers to identify hotspots and challenges and validate solution delivery.
• Technical leader with attention to detail, ensuring the AI teams are aligned with the strategic priorities, with a focus on talent development building the skills required.
• Motivates the team to participate internal events and hacks, and external competition like Kaggle, to build a culture of innovation and outside in perspective.
• Be a Strong coach and leader, build career development plans, engage and retain the talents, create a talent pipeline based on planned demands.
• Technical coach and mentor to handle a diverse team of AI talents across locations, in a matrix set up, and drive objectives and implementations.

Essential Skills/Experience:

• Master, in Computer Science, Mathematics, Data Science, Statistics or related subjects

15 years of experience working in the IT industry, data or AI related background. Knowledge of pharmaceutical business processes is required,

• 5+ years of experience and demonstrable technical skills in one or more of the following areas:

- Good understanding of Machine Learning and Deep Learning techniques, including Neural Networks, Natural Language Processing, and Computer Vision
- Demonstrate understanding and prior experience in multiple of these areas: Supervised, Unsupervised, Reinforcement, Self-Supervised, Semi-Supervised Learning
- Proficient in at least one Deep Learning framework, such as PyTorch, TensorFlow or JAX
- Prior experience in designing, analysing, training and fine-tuning neural networks, including CNNs, RNNs, Transformers

• Experienced in deploying machine learning models in production environments, including containerization (Docker) and orchestration (Kubernetes) and optimizing model hyperparameters to improve model performance.
• Distributed computing \xe2\x80\x93 familiarity for using Job Schedulers or HPC environments and training models using data/model/pipeline parallel training procedures.
• Proficiency in version control systems such as Git for collaboration and code management. Strategies to deal with poor and often highly heterogenous data.
• Good understanding of enterprise IT, including security, privacy, Architecture standards, quality management, testing etc
• Experience running enterprise technology projects, including engagement with technical and non-technical stakeholders.
• Ability to work with loosely defined objectives and turning these into requirements and business cases for enterprise investment
• Collaborative, having worked in a Hub Spoke matrix model, liaising with hubsite leads across capabilities.
• Ability to work with multi-functional and remote teams, nurturing young talents, creating a ready talent pipeline with experience / awareness to latest tools and industry practices
• Good written and verbal skills, fluent English.

Desirable Skills/Experience:
NIL

When we put unexpected teams in the same room, we unleash bold thinking with the power to inspire life-changing medicines. In-person working gives us the platform we need to connect, work at pace and challenge perceptions. That\xe2\x80\x99s why we work, on average, a minimum of three days per week from the office. But that doesn\'t mean we\xe2\x80\x99re not flexible. We balance the expectation of being in the office while respecting individual flexibility. Join us in our unique and ambitious world.

Why AstraZeneca:

Disrupt an industry and change lives. Here our work has a direct impact on patients, transforming our ability to develop life-changing medicines. We empower the business to perform at its peak and lead a new way of working, combining cutting-edge science with leading digital technology platforms and data. All with a passion to impact lives through data, analytics, AI, machine and more. Join us at a crucial stage of our journey in becoming a digital and data-led enterprise. Make the impossible possible by building partnerships and ecosystems, creating new ways of working and driving scale and speed to deliver exponential growth. Focused and committed, and backed with the investment to succeed, we\'re driving cross-company change to disrupt the entire industry.

Call to Action:
Are you ready to make a meaningful impact in the world of healthcare? Apply now and join our diverse team of innovators at AstraZeneca!

Date Posted 18-Jan-2024

Closing Date 25-Jan-2024

AstraZeneca embraces diversity and equality of opportunity. We are committed to building an inclusive and diverse team representing all backgrounds, with as wide a range of perspectives as possible, and harnessing industry-leading skills. We believe that the more inclusive we are, the better our work will be. We welcome and consider applications to join our team from all qualified candidates, regardless of their characteristics. We comply with all applicable laws and regulations on non-discrimination in employment (and recruitment), as well as work authorization and employment eligibility verification requirements.

AstraZeneca