Data Scientist / AI Engineer

Job Requirements :

• Bachelor's degree in Mathematics, Statistics, Computer Science, Engineering, or other related fields;
• Required to know Apache Spark, Hadoop, and MongoDB to manage it all;
• Have minimum 3 years experiences, preferably in Financial Service or Financial Technology Environment;
• Proven work experience as a AI Engineer, Data Scientist, or in a similar role;
• Proficiency in programming languages such as Python, Java, or Scala;
• Experience with data processing frameworks such as Apache Hadoop, Spark, or Flink, In-depth knowledge of SQL and NoSQL databases;
• Required to know Probability, statistics, and linear algebra: These are needed to implement different AI and machine learning models;
• Required to know Algorithms and frameworks: such as linear regression and Naive Bayes, as well as deep learning algorithms such as recurrent neural networks and generative adversarial networks and be able to implement them with a framework. Common AI frameworks include Theano, TensorFlow, Caffe, Keras, and PyTorch;
• Familiarity with cloud services, such as AWS, Azure, or Google Cloud Platform;
• An ability and eagerness to constantly learn and teach others;
• Ability to work independently in a professional and teamwork driven setting;
• Self-motivated, work quickly and accurately, and able to adapt to changing conditions.

Preferred Qualifications :

• Experience related fields with 2+ years academic/industrial experience in AI/ML/NLP based software development;
• Experience with one or more general purpose programming languages including but not limited to: JS, Python, Golang or C/C++;
• Experience in the development of production-level AI application leveraging various LLMs (including prompt engineering best practices);
• Exposure to Deep Learning, NLP, LLM, or related fields and a strong interest and desire to learn about them.

Job Descriptions :

• Design and Develop AI Models : AI Engineers create and validate algorithms, neural networks, and other machine learning techniques. They design and develop AI models from scratch, ensuring they simulate human intelligence processes;
• Implement AI Solutions : These professionals integrate AI solutions with existing business systems to enhance functionality and user interaction. They write code and deploy models to production environments;
• Manage Data Flow and Infrastructure : AI Engineers handle data flow and infrastructure to ensure effective AI deployment. This involves setting up data pipelines, managing storage, and optimizing performance;
• Collaborate Across Teams : They work closely with cross-functional teams to align AI initiatives with organizational goals. Collaboration with data scientists, software engineers, and other stakeholders is essential.