Junior Machine Learning Engineer

The Role: We are building an innovative Generative AI application that empowers enterprises by leveraging Large Language Models (LLMs) to scout and suggest startups that align with their technology and industry priorities. As a Junior Machine Learning Engineer, you will play a critical role in developing and implementing the machine learning models and algorithms that drive this app. You will work closely with our development team and product managers to ensure that the AI components are accurate, efficient, and scalable.

Key Responsibilities:

• Model Development & Integration: Assist in designing, developing, and integrating machine learning models, particularly LLMs, to match enterprise inputs with relevant startups.
• Data Handling & Preprocessing: Work on data collection, cleaning, and preprocessing to ensure high-quality input data for training models.
• Algorithm Optimization: Collaborate with senior engineers to optimize the performance of LLMs and other machine learning algorithms, ensuring they run efficiently on our platform.
• API Development: Contribute to the development of APIs that allow for seamless integration of the ML models with the app's frontend and other backend services.
• Testing & Validation: Implement testing frameworks to validate the accuracy and reliability of the models, including A/B testing and other evaluation methodologies.
• Collaboration: Work closely with the development team to align ML components with the overall app architecture, ensuring smooth integration and functionality.
• Documentation: Maintain clear and comprehensive documentation of the ML models, data handling processes, and API integrations to support ongoing development and future enhancements.
• Continuous Learning: Stay up to date with the latest advancements in machine learning, particularly in the domain of LLMs, and bring new ideas and techniques to the team.

Requirements:

• Preferably bachelor’s degree in computer science, Engineering, Mathematics, or a related field.
• Strong understanding of machine learning fundamentals, with hands-on experience in building and deploying ML models.
• Familiarity with Python and ML frameworks like TensorFlow, PyTorch, or similar.
• Experience with Large Language Models (LLMs) is a plus.
• Basic knowledge of API development and data handling best practices.
• Good problem-solving skills and the ability to work collaboratively in a fast-paced environment.
• Eagerness to learn and adapt to new technologies and methodologies.