Machine Learning Researcher - SaasGuru, Delhi & Mumbai

SaasGuru is seeking a highly motivated and proactive Machine Learning Researcher to join our mission-driven team. This role requires 2-5 years of experience and a strong foundation in machine learning and artificial intelligence. You will be instrumental in architecting and refining simulation models, leading cutting-edge research initiatives, and translating complex research findings into practical, deployable solutions that enhance our Ed-Tech offerings.

Roles and Responsibilities

• Research and Development: Architect and enhance sophisticated simulation models to achieve unparalleled accuracy. Spearhead research initiatives focused on advancing behavioral prediction science. Design and execute rigorous experiments to validate novel methodologies.
• Implementation: Transform research insights into tangible, deployable solutions. Collaborate closely with cross-functional teams to integrate advanced Machine Learning capabilities into our core product.
• Model Deployment: Leverage your expertise to successfully deploy Machine Learning models into production environments for real-world application and impact.

Skills Required

• Machine Learning & AI Expertise: Deep understanding of machine learning, with a focus on behavioral prediction, reinforcement learning, or probabilistic modeling. Proven hands-on experience in designing and implementing ML models for real-world scenarios is essential.
• Research & Experimentation: Demonstrated ability to conduct robust research, design effective experiments, and validate new AI and behavioral modeling approaches. A history of published work in relevant academic fields is advantageous.
• Software Development & Deployment: Proficiency in Python and leading ML frameworks such as TensorFlow, PyTorch, or scikit-learn. Essential experience in deploying ML models into production environments.
• Cloud & Scalable Systems: Familiarity with cloud-based ML platforms including AWS, GCP, or Azure, and scalable computing frameworks like Spark or Kubernetes, or other distributed computing environments.
• Cross-Functional Collaboration: Strong ability to collaborate effectively with product teams, data engineers, and other stakeholders to seamlessly integrate advanced AI capabilities into user-centric solutions.