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AstraZeneca

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4.1

based on 795 Reviews

122 AstraZeneca Jobs

Senior AI Engineer

AstraZeneca India Pvt. Ltd

4.1

based on 795 Reviews

5-10 years

Bangalore / Bengaluru

1 vacancy

Senior AI Engineer

AstraZeneca

posted 7hr ago

Job Role Insights

Flexible timing

Key skills for the job

Computer Science Python Artificial Intelligence Machine Learning Project Management Recruitment

+ 2 more

Job Description

This role will allow you to develop, maintain and productionize AI solutions across our business areas. You will be responsible for packaging solutions and code bases, building machine learning pipelines, maintaining existing AI/ML solutions, and using up-to-date data science, artificial intelligence and cloud technologies to scale solutions systematically.

Accountabilities:

As an Associate Director, AI Engineer, you will be part of our Clinical Data & Insights Team. Your role 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. You will provide technical leadership in the aspects of machine learning and AI solution engineering, collaborate with cross-functional teams, stay updated on the latest developments in AI and related technologies, and drive research efforts to explore new machine learning and AI techniques.

Essential Skills/Experience:

Bachelors 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 handling 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 e.g., 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 (e.g., Docker, Kubernetes).
Knowledge of cloud platforms (e.g., AWS, Azure, GCP) and modern DevOps practices.
Proficiency in security standard methodologies, 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 collaborators.
Experience in software engineering and machine learning standard methodologies, including version control, continuous integration (CI) and continuous development (CD), containerization, and shell scripting.
Creative, collaborative, & product focused.