Qualitative Financials
Machine Learning Engineer
Qualitative Financials, Sunnyvale, California, 94087
Machine Learning Engineer Visa : Any Expereince : 7 Location: Sunnyvale, CA (Remote) Contract : W2 Job Description: We are seeking a highly skilled and experienced Senior Machine Learning Engineer to join our team at Sam's Club. As a Senior Client Engineer, you will be responsible for developing and implementing advanced machine learning models and algorithms to enhance our retail operations. Your work will directly impact customer experience, inventory management, pricing optimization, demand forecasting, and fraud detection, among other critical areas. If you have a passion for cutting-edge technology, a strong background in machine learning, and a desire to drive innovation in the retail industry, this is the perfect opportunity for you. About Team: Supply Chain at Sam's Club is all about delivering plans that help provide our members with the products they want, where they want them, at the best price possible. To accomplish this, associates must think critically and create efficiencies, using data and experience to overcome complex challenges. We invite you to join the Sam's Club Supply Chain Team; a quick moving group of motivated individuals with skills ranging from data analytics to strategy and execution. Together we will design the supply chain of the future and improve our members' lives. What you'll do: - Collaborate with cross-functional teams, including data scientists, software engineers, and product managers, to understand business requirements and translate them into machine learning solutions. - Deploy and monitor machine learning and optimization models to solve complex retail problems such as customer segmentation, recommendation systems, personalized marketing, and supply chain. - Implement best practices of MLOps to ensure product health - Apply state-of-the-art techniques in deep learning, natural language processing, reinforcement learning, and computer vision to drive innovation and improve business performance. - Design and implement scalable and efficient algorithms to process large-scale datasets, ensuring robustness, accuracy, and scalability. - Analyze and interpret the results of Client models, providing actionable insights and recommendations to stakeholders. - Collaborate with data engineers to ensure the availability, quality, and reliability of data required for machine learning models. - Collaborate with Developer AI Platform teams to enable delivery of new Generative AI capabilities. - Stay up-to-date with the latest advancements in machine learning and retail industry trends, proactively identifying opportunities for improvement and innovation. - Mentor and guide junior team members, fostering a culture of knowledge sharing and continuous learning. What you'll bring: - Bachelor's or Master's degree in Computer Science, Data Science, or a related field. - 3 years of industry experience working as a Machine Learning Engineer, ideally in the retail sector. - Strong programming skills in Python/Java. - Demonstrated expertise in developing and deploying machine learning models at scale. - Demonstrated expertise in developing and deploying machine learning models at scale. - Solid understanding of deep learning architectures, natural language processing, and computer vision techniques. - Experience with prompt engineering - Experience with deep learning/LLM-based products or platforms. - Proficiency in data manipulation, feature engineering, and model evaluation. - Experience working with big data technologies and distributed computing frameworks (e.g., Hadoop, Spark). - Experience with design and architecture, and with testing/launching software products. - Excellent problem-solving and analytical thinking abilities, with a strong attention to detail. - Strong communication and collaboration skills, with the ability to effectively convey complex ideas to both technical and non-technical stakeholders. - Proven track record of delivering high-quality machine learning solutions in a fast-paced, agile environment