[SX] Senior AI Engineer

Job Description

• Department Collaboration: Work closely with various internal Departments to identify their pain points and evaluate the feasibility of applying AI/GenAI solutions to address these challenges.
• Large Language Models (LLMs): Utilize Large Language Models, including open-source models from Hugging Face and Azure OpenAI, to develop sophisticated language-based applications.
• Algorithm Development: Design, develop, and implement advanced AI algorithms and models with a focus on generative AI solutions.
• Coding Excellence: Write and optimize high-quality Python code to create efficient AI models and applications.
• Machine Learning Expertise: Apply deep knowledge of machine learning and deep learning techniques to solve real-world problems.
• Computer Vision: Develop and deploy computer vision solutions, particularly on edge devices such as Raspberry Pi and Jetson Nano.
• Data Analysis: Perform comprehensive data analysis on time-series data to uncover trends, anomalies, and insights.
• Solution Automation: Create automation solutions leveraging AI capabilities, including generative AI models.
• Deployment: Deploy AI solutions on both on-premises servers and cloud environments, with a focus on Azure and private cloud.
• Team Leadership: Provide guidance, set goals, and offer technical solutions for AI and generative AI projects while leading team members.

Qualifications

• Education: Master’s or bachelor’s degree in Computer Science, Mathematics, or a related field.
• Experience: Minimum of 3-5 years of experience in AI/ML, with a proven track record in the outlined key responsibilities.

Additional Information

• Programming Proficiency: Expertise in Python and relevant libraries (e.g., TensorFlow, PyTorch, Scikit-learn, Pandas, transformers, LangChain, llama-index).
• Mathematical and Analytical Skills: Strong skills in mathematical, programming, and statistical analysis.
• Machine Learning and Deep Learning: Advanced knowledge in machine learning and deep learning techniques.
• Computer Vision: Hands-on experience with computer vision technologies and edge devices.
• Data Analysis: Proficient in data analysis, particularly time-series analysis.
• Automation Solutions: Experience in developing and implementing automation solutions using AI.