Duties/Responsibilities
The AI Software Engineer will be responsible for creating deployable versions of all Machine Learning models and integration of these into products for improving health and well-being. They will join APHRC’s multidisciplinary team to help in shaping new strategy and showcasing the potential for AI through early-stage solutions.
The AI Software Engineer will:
Develop ML models alongside DSE’s data engineers, data analysts, data scientists and provide provide end to end AI solutions;
Build Code Infrastructure from ML models developed by data scientists in DSE using advanced technologies;
Package ML models into usable products by researches and policy makers;
Create End Point APIs from the ML algorithms. These will include products such mobile applications, web services, chatbots, CDSS etc.;
Develop the development of platform for data sharing;
Provide updates on breakthrough artificial intelligence technologies with the potential to transform the Center’s research environment, the research staff or policy makers’ experience and influence policy development and decision making;
Work closely with DSE data engineers, program and data managers to produce data into usable formats for analysis;
Prepare and support monthly reports and scientific publications;
Support data managers in the use of the metadata software programs;
Develop training curricula and training materials;
Attend DSE technical and progress meetings; and
Contribute to report and manuscript writing, knowledge translation products, grants, and ethics review board applications.
Qualifications, Skills, and Experience
PhD in Data science, Applied Mathematics, Computational Science and Engineering, Applied Statistics. Master’s degree in Computer Science, Data Science, Software Development, or other related field.
At least three years of experience formulating and strategizing AI solutions; with at least one-year’s postdoctoral experience.
Solid understanding of common programming languages used in AI, such as Python, Java, C++, and R.
Advanced knowledge of statistical and algorithmic models as well as of fundamental mathematical concepts, such as linear algebra and probability.
Experience working with large data sets and writing efficient code capable of processing large data streams at speed.
Proven experience in applying AI to practical and all-inclusive technology solutions.
Hands-on knowledge in machine learning, deep learning, Tensorflow, Python, NLP.
Understanding of functional design principles, object-oriented programming principles, basic algorithms.
Expertise in REST API development, NoSQL design, RDBMS design.
Proven expertise in using deep learning, neuro-linguistic programming (NLP), computer vision, chatbots, and robotics to help the internal teams promote diverse research outcomes and drive innovation is a must have.
Understanding of website scripts such as XML, Javascript, JSON.
Understanding of ETL framework and ETL tools including Alteryx and Microsoft SSIS.
Digital marketing analytics tools including Google 360, Google Analytics, Google Tag Manager and Adobe Marketing Suite.
Experience with data visualization tools like R shiny, matplotlib, ggplot, d3.js.ArcGIS, QGIS, Tableau to visually encode data and generation of dashboards for interpretation.
Good communication skills to describe findings to both technical and non-technical audiences.
Excellent problem-solving skills, self-driven, has attention to detail with a strong analytical mind.
Demonstrate ability to work both independently and to work collaboratively with internal and external team members, and stakeholders.
Ability to multi-task, work accurately and effectively to deadlines; has good self-assessment of timing of tasks and ability to set deadlines. Organizational and time management skills to manage and prioritize workload.
Demonstrate an appreciation of technical and analytic challenges, and learning new approaches and topics.
Deadline: March 31, 2023
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