The AI/ML Engineer will be responsible for designing, developing, and deploying machine learning models and AI solutions. You will work closely with cross-functional teams to create and implement algorithms and systems that drive our technology forward. The ideal candidate will have a strong background in AI and machine learning, with expertise in Python, SQL, Java, and experience with generative AI and chatbots.
Key Responsibilities:
- Model Development: Design, develop, and implement machine learning models and algorithms to solve complex problems.
- Data Analysis: Utilize SQL to extract, manipulate, and analyze data from various sources to support model training and evaluation.
- Software Engineering: Develop robust and scalable code in Python and Java to integrate AI/ML solutions into our existing systems and applications.
- Generative AI: Create and optimize generative AI models to generate content, predictions, or other outputs as required by the business.
- Chatbot Development: Design and implement conversational AI solutions and chatbots to enhance user interactions and automate processes.
- Collaboration: Work closely with data scientists, software engineers, and product managers to understand requirements and deliver effective AI solutions.
- Performance Monitoring: Continuously monitor and improve the performance of deployed models, ensuring they meet the desired accuracy and efficiency.
- Research & Innovation: Stay up-to-date with the latest advancements in AI/ML and contribute to innovative projects and solutions.
Required Skills and Qualifications:
- Education: Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related field.
- Experience: Proven experience in AI/ML model development and deployment.
- Programming Languages: Proficiency in Python and Java.
- SQL: Strong skills in SQL for data extraction and manipulation.
- Generative AI: Experience with generative AI techniques and applications.
- Chatbots: Hands-on experience in developing and deploying chatbots and conversational AI systems.
- Machine Learning Frameworks: Familiarity with popular ML frameworks such as TensorFlow, PyTorch, or Scikit-learn.
- Problem-Solving: Excellent analytical and problem-solving skills with the ability to tackle complex challenges.
