Machine Learning Engineer

Machine Learning Engineer About the Company We are a fast-growing AI-driven platform focused on transforming the recruitment landscape. By using advanced machine learning models to predict human potential, we aim to help organizations identify the best candidates quickly and accurately. Our AI-powered system analyzes resumes, conducts AI-driven interviews, and leverages online profiles to rank candidates and match them with the ideal roles. From early-stage startups to leading AI labs, our technology is already helping companies make data-backed hiring decisions. We are looking for a Machine Learning Engineer to join our team and contribute to this mission. About the Role As a Machine Learning Engineer, youll play a pivotal role in building and optimizing the core of our platform: the AI models that rank candidates for job relevance. You'll work with large-scale proprietary datasets to develop, deploy, and improve sophisticated machine learning models. This role is perfect for someone with a deep understanding of machine learning techniques, strong programming skills, and a practical approach to model iteration and deployment. You'll also have the chance to collaborate closely with other teams to ensure that our machine learning systems integrate seamlessly with our broader product offering. What We Can Offer You Competitive salary and equity options Opportunity to work on cutting-edge AI technology in a high-impact role Exposure to large-scale, real-world machine learning applications Work in a collaborative, fast-paced environment with a talented team Flexibility in work hours and location Key Responsibilities Develop Advanced Algorithms: Build, test, and deploy sophisticated machine learning models, including learn-to-rank (LTR) models, semantic search algorithms, and models that integrate multimodal interview data and historical performance data. Optimize Infrastructure: Write efficient, clean, and scalable code to ensure the platform can handle high-volume recruitment operations. Develop ML infrastructure for large-scale, multimodal data processing. Experimentation and Iteration: Lead rapid experimentation to improve model performance, focusing on speed and efficiency. Continuously iterate and refine models to adapt to evolving user needs. Bias Mitigation: Implement methods to measure and mitigate algorithmic bias, ensuring fairness and transparency in candidate evaluations. Cross-functional Collaboration: Work with product and engineering teams to integrate machine learning solutions into the broader product ecosystem. Contribute to the long-term ML strategy of the company. What Were Looking For B.S., M.S., or Ph.D. in Computer Science, Data Science, or a related technical field, with practical experience in machine learning. Strong programming skills in Python and experience with common ML libraries such as PyTorch. Hands-on experience with LTR or recommendation models and semantic search algorithms at scale. Familiarity with rapid iteration and experimentation in machine learning model development. Excellent problem-solving skills and the ability to write performant code that scales. Strong communication and collaboration skills, with an ability to work effectively within a team. Relevant Keywords: machine learning , learn-to-rank (LTR) , semantic search , multimodal data , AI models , algorithmic bias , recommendation systems , high-volume production environments , Python , PyTorch . If you have a passion for applying machine learning to real-world problems, enjoy collaborating in a fast-paced environment, and are excited by the opportunity to shape the future of AI-powered recruitment, wed love to hear from you.