AI ML Research Engineer

We are seeking an AI/ML Research Engineer with a profound passion for the field of artificial intelligence. This role is ideal for someone who views challenges as milestones waiting to be surpassed, who approaches problem-solving with both creativity and precision, and whose passion for AI and ML is matched by an outstanding technical skill set. You will lead the charge in developing state-of-the-art AI models, optimizing performance, and transitioning theoretical models into production-ready solutions.

Areas of Research

• Graph Self-Supervised Learning
• Temporal Graph Learning.
• Multi-modal graph representation learning
• HIIL DRL Techniques for conversational intelligence
• Mechanistic interpretation of LLMs
• Topological Deep Learning
• Cognitive Assessment using AI Techniques
• Autonomous Knowledge Graphs
• Neuro-symbolic AI
• AGI
• Federated Graph Neural Networks

Responsibilities

• Collaborate seamlessly within a multidisciplinary team of researchers to invent new technologies and algorithms based on identified needs, contributing to the company's cutting-edge advancements in the field.
• Uncover intricate patterns within data and apply advanced techniques to quantitatively analyze information.
• Map data into the appropriate machine learning algorithmic space, ensuring optimal representation for model development.
• Conceptualize and engineer machine learning and deep learning systems, pushing the boundaries of innovation in algorithmic design.
• Enhance and elevate existing state-of-the-art machine learning algorithms to address complex problems.
• Execute rigorous unit tests on developing packages, ensuring the reliability and robustness of the implemented solutions.
• Conduct comprehensive machine learning tests and experiments, leveraging a keen research mindset to explore novel approaches.
• Train and retrain systems as needed, incorporating adaptability and foresight into the continuous improvement process.
• Conduct thorough literature reviews, staying at the forefront of the latest developments in the specified research areas.
• Analyze and interpret research findings, actively contributing to the publication of groundbreaking research papers in prestigious conferences and journals.
• Engage proactively in regular team meetings to share progress, address challenges, and brainstorm potential improvements.
• Profound comprehension of data structures, algorithms, and software architecture, showcasing a strong foundation in computational principles.
• In-depth understanding of machine learning algorithms, reflecting a keen insight into the intricacies of advanced learning methodologies.
• Proven ability to thrive in a dynamic research environment, showcasing adaptability, curiosity, and a proactive approach to tackling complex challenges.
• Advanced knowledge of probability, statistics, and linear algebra, underlining a solid theoretical background crucial for cutting-edge research.
• Proficient in crafting robust Python code, highlighting the capacity to develop efficient and scalable solutions.
• Familiarity with leading machine learning libraries such as TensorFlow, PyTorch, and scikit-learn, illustrating a hands-on approach to leveraging state-of-the-art tools.
• Exceptional communication skills, enabling the effective dissemination of complex concepts to both technical and non-technical audiences.
• Collaborative spirit with a demonstrated ability to work seamlessly within a team, fostering an environment conducive to shared innovation.
• Outstanding analytical and problem-solving prowess, emphasizing a strategic and innovative mindset essential for pushing the boundaries of research in AI and related fields.