Associate Director of Engineering
Barcelona (ESP), Gothenburg (SWE), Cambridge (UK), Gaithersburg (US), Toronto (CAN)
Competitive Salary + Benefits
Make a more meaningful impact to patients’ lives around the globe
Here you’ll have the opportunity to make a meaningful difference to patients’ lives. With science at its heart, this is the place where breakthroughs born in the lab become transformative medicines – for the world’s most complex diseases. Answer unmet medical needs by pioneering the next wave of science, focusing on outcomes and shaping the patient ecosystem. With our ground-breaking pipeline, the outlook is bright. Be proud to be part of a place that has achieved so much, yet is still moving forward. There’s no better time to join our global, growing enterprise as we lead the way for healthcare and society
The Center for Artificial Intelligence (CAI) is a lab focused on applying machine learning research to the most challenging problems at AstraZeneca. We innovate together with our leading biologists, chemists, and clinicians to close the gap between today's challenges and the forefront of machine learning.
If you would like to have an impact on transforming patients' lives by accelerating new medicines to patients, this may be the position for you!
The team is looking for an Associate Director of Engineering to specialize in the optimization of engineering standards and practices within the team as it applies to our application of machine learning (ML) techniques to diverse scientific problems in health care.
The team makes use of advanced ML techniques including deep learning and knowledge graphs. This position will be pivotal in optimizing how these techniques are used, optimizing for rigor, reproducibility, speed and sustainability. Applicants should have a strong foundation in software and devops/mlops engineering in production ML systems.
The candidate should also have a strong knowledge of the drug development process in the pharmaceutical industry and experience maintaining a portfolio of ML enabled products. This position is an individual contributor role and will not involve line management of reports.
Collaborate with the team in setting a set of engineering standards, best practices, templates, documentation and learning material to socialize best engineering practice in the team.
Optimize computational processes in terms of utilization, distribution and data transfer speeds to lower total costs and environmental impacts.
Develop and maintain CI systems which increase overall speed of contribution to and quality of the team’s code base.
Develop CD systems which securely deploy ML based model endpoints and applications
Develop monitoring systems which feedback to ML engineers the real time performance and stability of model endpoints and applications.
Assist with release management within the team of ML models, applications and software packages.
Automate processes within the team to reduce the time spent on non-differentiating tasks.
Engage with IT teams to ensure any additional system requirements are accurately defined.
Collaborate with ML Engineers and scientists in other business units to suggest engineering solutions to scientific opportunities
Review working practices and ensures non-compliant processes are raised
Education, Qualifications, Skills and Experience
Bachelor’s degree in rigorous quantitative science (such as mathematics, computer science, engineering)
Demonstrated an outstanding track-record of industry experience (4+ years) using machine learning systems
At least 2 years of experience in a devops/mlops team in the pharmaceutical industry
Software engineering experience in python or other relevant language, including CI/CD and gitops
Hands on experience using AWS infrastructure
Hands on experience using open-source products for machine learning on kubernetes, in particular kubeflow
Experience in advanced containerization techniques
End-to-end experience implementing machine learning projects in an industry setting
Knowledge of model operations including model tracking, model governance, multiple models in different production contexts
Knowledge of range of machine learning techniques and drive to continue to learn and develop these skills.
Communication, business analysis, and consultancy; ability to present compelling cases to partners and operate dynamically to identify solutions
Ph.D. or M.Sc. degree in rigorous quantitative science (such as mathematics, computer science, engineering) or M.B.A. with analytics experience in industry.
AWS or Kubernetes certifications
Why AstraZeneca?
At AstraZeneca we’re dedicated to being an excellent Place to Work. Where you are empowered to push the boundaries of science and unleash your ambitious spirit. There’s no better place to make a difference to medicine, patients and society.
An inclusive culture that champions diversity and collaboration, and always committed to lifelong learning, growth and development. We’re on an exciting journey to pioneer the future of healthcare.
Why we love it
If your passion is science and you want to be part of a team that makes a bigger impact on patients’ lives, then there’s no better place to be. Here we truly understand science and apply it every day to strengthen and grow our pipeline.
So, what’s next?
Are you already imagining yourself joining our team? Good, because we can’t wait to hear from you.
Are you ready to bring new ideas and fresh thinking to the table? Brilliant! We have one seat available and we hope it’s yours.
Where can I find out more?
Our Social Media, Follow AstraZeneca on LinkedIn
Follow AstraZeneca on Facebook https://www.facebook.com/astrazenecacareers/
Follow AstraZeneca on Instagram https://www.instagram.com/astrazeneca_careers/?hl=en
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Date Posted
01-Nov-2022
Closing Date
01-Dec-2022
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 requires all US employees to be fully vaccinated for COVID-19 but will consider requests for reasonable accommodations as required by applicable law.
