Applied Scientist

Position : Applied Scientist Location: USA/Canada – Remote DESIGNATION Applied Scientist As an Applied Scientist, you will be responsible for designing, developing, and deploying machine learning and Al solutions that directly impact product innovation and user experience. You will collaborate with cross-functional teams including product managers, engineers, and researchers to integrate cutting-edge Al technologies into scalable systems. ROLE DESCRIPTION: Algorithm Development: Design and implement state-of-the-art ML and deep learning algorithms for tasks such as recommendation, search, NLP, and computer vision Applied Research: Conduct hands-on research into new Al/ML methodologies, particularly in generative models like GANS, VAES, and LLMs, to solve emerging business challenges. Prototyping & Deployment: Rapidly prototype new ideas, test hypotheses, and build robust, production-ready features or products that integrate these models Product Integration: Work closely with engineering and product teams to integrate Al models into production systems, ensuring performance, scalability, and reliability. Experimentation: Design and run experiments to validate hypotheses and measure model effectiveness. Use metrics-driven approaches to refine and optimize solutions. Collaboration: Partner with stakeholders across Windows, Outlook, Teams, Edge, and Bing to deliver unified Al experiences. Customer Impact: Translate business needs into technical solutions that improve user engagement, retention, and satisfaction SKILLS 8-12+ years of working experience as Applied Scientist, with at least 2-4 years in generative AL, ML & RAG systems. Master's, or Ph.D. in Computer Science, Electrical Engineering, Statistics, or related field. Strong programming skills in Python, C++, Java, or similar languages. Experience with ML frameworks such as PyTorch, TensorFlow, Scikit-learn. Experience with Large Language Models (LLMs), NLP, and recommendation systems. Proven track record of shipping ML models to production. Experience in training and deploying generative Al models, optimizing models for efficiency, and managing large-scale infrastructure. Experience with Azure cloud services Excellent problem-solving and analytical skills. Strong communication and collaboration abilities across teams. Publications in top-tier conferences (e.g., NeurIPS, ICML, ACL). Experience with high-scale systems and distributed computing. Exposure to agentic technologies and generative Al frameworks