Senior Analyst - AI Engineer
We are looking for a AI Engineers to join our AI Engineering team in Chennai. The ideal candidate will have industry experience working on a range of different natural language processing disciplines, e.g. search ranking, text/sentiment classification, deep learning and others. The position will involve taking these skills and applying them to some of the most exciting data & prediction problems in drug discovery. You will work as part of a global team of deeply technical data scientists, knowledge engineers & machine learning engineers and have the chance to create tools that will advance the standard of healthcare improving the lives of millions of patients across the globe.
We are working in collaboration with our scientists to help develop better drugs faster, choose the right treatment for a patient and run safer clinical trials. Our team empowers our scientists from early development to the late stages in drug development, driving innovation and acting as a catalyst for the adoption of the latest advances in Artificial Intelligence and Data Science. You will work closely with scientists & product teams and learn to deliver NLP solutions at scale within the AstraZeneca tech stack, whilst encouraging best practices for NLP across the company.
We are looking to build NLP-based systems, tools, and services that serve as infrastructure for practically everyone in AstraZeneca. As a strong software leader and an expert in building complex systems, you will be responsible for inventing how we use technology, natural language processing and text to enable the productivity of AstraZeneca.
You will help envision, build, deploy and develop our next generation of NLP engines and tools at scale.
- Maintain and Support the AI models which are deployed in production
- Periodically Re-train, Deploy the AI models in Cloud and improve the performance of the models
- Adapt standard machine learning methods to best exploit modern parallel environments (e.g. distributed clusters, multicore SMP, and GPU)
- Deploying NLP solutions into production.
- Optimizing solutions for performance and scalability.
- Data engineering, i.e. ensuring a good data flow between database and backend systems with high performance data pipelines.
- Liaise with other teams to enhance our technological stack, to enable the adoption of the latest advances in Data Processing and AI
- Being an active member of the AI Engineering team, you will benefit from, and contribute to, our expanding bank of Data Science algorithms and work efficiently with our data science infrastructure. You will get involved in testing and assessing the quality of new tools. It’s also likely you’ll get involved in team recruitment, training provision and coaching
Candidate Knowledge, Skills and Experience
- Experience in one or more of the following areas: machine learning, natural language processing and computer vision.
- Experience in using unsupervised and supervised methods over unstructured data: especially with search and text analytics.
- Knowledge of scraping documents and document extraction key.
- Strong software development skills, with proficiency in Python preferred
- Experience building large scale data processing pipelines
- Experience with Cloud computing, Hadoop/Spark, SQL
- Ability to explain and present analyses and machine learning concepts to a broad technical audience
- Creative, collaborative, & product focused
- Use of Data Science Modelling Tools eg. Python, Hadoop, Spark, SAS and Data Science Notebooks (e.g. Jupyter)
- Experience with filesystems, server architectures, and distributed systems
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 authorisation and employment eligibility verification requirements.