6 Multiarmed Bandits Jobs

As the Principal Machine Learning Scientist at Nykaa's AdTech Data Science team, you will play a crucial role in developing intelligent, ML-powered advertising products such as Sponsored Products, Display Ads, and Creative Personalization. Your primary responsibility will be to lead the development of foundational ML models and systems that drive the ad platform, collaborating closely with product, engineering, and business teams to address high-impact problems in advertising science. You should have a solid educational background with a Bachelors, Masters, or Ph.D. in Computer Science, Machine Learning, Statistics, or a related technical field from a reputable institution. With over 10 years of experience in building production-grade ML systems, including at least 5 years in AdTech, performance marketing, or large-scale recommender systems, you should have a proven track record of delivering impactful ML innovations as a senior individual contributor. Your technical expertise should encompass domains such as CTR/CVR prediction, bidding dynamics, bid/budget optimization, multi-objective learning, campaign automation, target ROAS modeling, and generative AI for creative optimization. Proficiency in ML algorithms, reinforcement learning, Bayesian optimization, and game theory as applied to digital advertising is essential, along with fluency in Python and ML frameworks like PyTorch, TensorFlow, XGBoost, and libraries like LightGBM and Scikit-learn. In addition to technical skills, you should possess a passion for solving complex problems with scientific rigor and business impact, along with a deep ownership mentality and the ability to drive projects independently. Effective communication of technical concepts to cross-functional stakeholders, collaborative mindset, and a track record of influencing product direction through technical thought leadership are also crucial soft skills for this role. Your responsibilities will include designing and developing cutting-edge models for predicting ad outcomes, building intelligent automation systems for campaign management, developing generative models for optimizing ad creatives, owning the architecture of core components within the ad platform, and collaborating with Product and Engineering teams to design ML-first features that are measurable. Additionally, you will explore and prototype novel approaches using Reinforcement Learning, RLHF, contrastive learning, or LLMs for advertiser assistance or campaign agents, and contribute to thought leadership and innovation through internal whitepapers and external publications. Joining Nykaa's AdTech team will offer you the opportunity to be a key technical architect behind the company's growing AdTech ecosystem, work on cutting-edge problems at the intersection of ML, economics, personalization, and creative optimization, and shape the future of advertising on India's leading beauty and lifestyle platform with a focus on user delight and advertiser success.,

You will be joining Wayfair's Advertising business, which is experiencing rapid growth and adding substantial profits to the company. The team is focused on building Sponsored Products, Display & Video Ad offerings to meet various advertiser goals and provide engaging Ads to millions of customers. As part of the team, you will contribute to evolving the Ads Platform to empower advertisers of all levels to achieve a strong ROI through state-of-the-art Machine Learning techniques. The Advertising Optimisation & Automation Science team plays a crucial role in this effort by utilizing machine learning and generative AI to streamline campaign workflows and provide impactful recommendations on budget allocation, target Return on Ad Spend (tROAS), and SKU selection. Additionally, the team is working on developing intelligent systems for creative optimization and exploring agentic frameworks to simplify and enhance advertiser interactions. As a Senior Machine Learning Manager, you will lead a growing team dedicated to building intelligent, ML-powered systems that drive personalized recommendations and campaign automation within Wayfair's advertising platform. You will have the opportunity to define and deliver innovative capabilities that create substantial commercial value and directly improve advertiser outcomes. Collaborating with a team of ML scientists and engineers, you will tackle challenging problems in machine learning, latency, and scalability while contributing to the company's success. Key Responsibilities: - Own the strategy, roadmap, and execution of supplier advertising intelligence and automation solutions. - Lead the development of GenAI-powered creative optimization, ML-based recommendation systems, and campaign automation to drive incremental ad revenue and enhance supplier outcomes. - Build and manage a team of ML scientists focused on developing intelligent budget, tROAS, and SKU recommendations, creative testing frameworks, and simulation-driven decision-making. - Collaborate cross-functionally with Product, Engineering, and Sales teams to deliver scalable ML solutions that enhance supplier campaign performance. - Research and implement best practices in advertising science, GenAI applications, and auction modeling to keep Wayfair at the forefront of innovation. - Collaborate with Engineering teams to build and scale the infrastructure required for automated, intelligent advertising decision-making. - Provide mentorship and technical guidance to the broader DS/Eng organization as a subject matter expert when needed. Requirements: - Bachelor's or Master's degree in Computer Science, Mathematics, Statistics, or related field. - 10+ years of industry experience, with 1-2 years as a manager and 5+ years as an IC on production ML systems. - Strategic thinker with a customer-centric mindset and a passion for creative problem-solving. - Strong communication skills and ability to influence senior stakeholders based on data-driven recommendations. - Proficiency in programming languages such as Python, Golang, or Rust. Nice to have: - Experience with GCP, Airflow, and containerization (Docker). - Experience building scalable data processing pipelines with big data tools. - Familiarity with Generative AI and agentic workflows. - Experience in Bayesian Learning, Multi-armed Bandits, or Reinforcement Learning.,

Candidates for this position are preferred to be based in Bangalore and will be expected to comply with their team's hybrid work schedule requirements. Wayfair is moving the world so that anyone can live in a home they love a journey enabled by more than 3,000 Wayfair engineers and a data-centric culture. Wayfair's Advertising business is rapidly expanding, adding hundreds of millions of dollars in profits to Wayfair. We are building Sponsored Products, Display & Video Ad offerings that cater to a variety of Advertiser goals while showing highly relevant and engaging Ads to millions of customers. We are evolving our Ads Platform to empower advertisers across all sophistication levels to grow their business on Wayfair at a strong, positive ROI and are leveraging state-of-the-art Machine Learning techniques. The Advertising Optimization & Automation Science team is central to this effort. We leverage machine learning and generative AI to streamline campaign workflows, delivering impactful recommendations on budget allocation, target Return on Ad Spend (tROAS), and SKU selection. Additionally, we are developing intelligent systems for creative optimization and exploring agentic frameworks to further simplify and enhance advertiser interactions. We are looking for an experienced Senior Machine Learning Scientist to join the Advertising Optimization & Automation Science team. In this role, you will be responsible for building intelligent, ML-powered systems that drive personalized recommendations and campaign automation within Wayfair's advertising platform. You will work closely with other scientists, as well as members of our internal Product and Engineering teams, to apply your ML expertise to define and deliver 0-to-1 capabilities that unlock substantial commercial value and directly enhance advertiser outcomes. What You'll do: - Design and build intelligent budget, tROAS, and SKU recommendations, and simulation-driven decisioning that extends beyond the current advertising platform capabilities. - Lead the next phase of GenAI-powered creative optimization and automation to drive significant incremental ad revenue and improve supplier outcomes. - Raise technical standards across the team by promoting best practices in ML system design and development. - Partner cross-functionally with Product, Engineering, and Sales to deliver scalable ML solutions that improve supplier campaign performance. Ensure systems are designed for reuse, extensibility, and long-term impact across multiple advertising workflows. - Research and apply best practices in advertising science, GenAI applications in creative personalization, and auction modeling. Keep Wayfair at the forefront of innovation in supplier marketing optimization. - Collaborate with Engineering teams (AdTech, ML Platform, Campaign Management) to build and scale the infrastructure needed for automated, intelligent advertising decisioning. We Are a Match Because You Have: - Bachelor's or Masters degree in Computer Science, Mathematics, Statistics, or related field. - 9+ years of experience in building large scale machine learning algorithms. - 4+ years of experience working in an architect or technical leadership position. - Strong theoretical understanding of statistical models such as regression, clustering and ML algorithms such as decision trees, neural networks, transformers and NLP techniques. - Proficiency in programming languages such as Python and relevant ML libraries (e.g., TensorFlow, PyTorch) to develop production-grade products. - Strategic thinker with a customer-centric mindset and a desire for creative problem solving, looking to make a big impact in a growing organization. - Demonstrated success influencing senior level stakeholders on strategic direction based on recommendations backed by in-depth analysis; Excellent written and verbal communication. - Ability to partner cross-functionally to own and shape technical roadmaps - Intellectual curiosity and a desire to always be learning! Nice to have: - Experience with GCP, Airflow, and containerization (Docker). - Experience building scalable data processing pipelines with big data tools such as Hadoop, Hive, SQL, Spark, etc. - Familiarity with Generative AI and agentic workflows. - Experience in Bayesian Learning, Multi-armed Bandits, or Reinforcement Learning.,

As a Senior Machine Learning Manager at Wayfair's Advertising Optimization & Automation Science team, you will play a pivotal role in leading a team dedicated to developing intelligent, ML-powered systems that drive personalized recommendations and campaign automation within Wayfair's advertising platform. Your responsibilities will involve owning the strategy, roadmap, and execution of supplier advertising intelligence and automation solutions. You will lead initiatives focused on GenAI-powered creative optimization, ML-based recommendation systems, and campaign automation to drive significant incremental ad revenue and improve supplier outcomes. In this role, you will build, coach, and manage a team of ML scientists who will work on developing intelligent budget, target Return on Ad Spend (tROAS), and SKU recommendations, as well as creative testing frameworks and simulation-driven decision-making processes. Collaboration with cross-functional teams such as Product, Engineering, and Sales will be essential to deliver scalable ML solutions that enhance supplier campaign performance. Your expertise will be crucial in ensuring that systems are designed for reuse, extensibility, and long-term impact across multiple advertising workflows. Furthermore, you will be involved in researching and applying best practices in advertising science, GenAI applications in creative personalization, and auction modeling to keep Wayfair at the forefront of innovation in supplier marketing optimization. Collaboration with Engineering teams will also be a key aspect of your role to build and scale the necessary infrastructure for automated, intelligent advertising decision-making. To be successful in this position, you should have a Bachelor's or Masters's degree in Computer Science, Mathematics, Statistics, or a related field, along with 9+ years of industry experience. Additionally, you should have at least 1-2 years of experience as a manager of teams and 5+ years serving as an Individual Contributor (IC) on production ML systems. Proficiency in programming languages such as Python, Golang, or Rust is required, and experience with GCP, Airflow, and containerization is a plus. If you are a strategic thinker with a customer-centric mindset, excellent communication skills, and a passion for creative problem-solving, this role offers you the opportunity to make a significant impact in a rapidly growing organization like Wayfair. Join us in reinventing the way people shop for their homes and embark on a rewarding career journey filled with growth, learning, and dynamic challenges. Please note that your personal data will be processed in accordance with Wayfair's Candidate Privacy Notice. For any inquiries or to exercise your privacy rights, please contact dataprotectionofficer@wayfair.com.,

As a Senior ML Scientist in the Advertising Optimization & Automation Science team at Wayfair, you will play a crucial role in leveraging machine learning and generative AI to streamline campaign workflows. Based in Bangalore, India, you will contribute to building intelligent systems that drive personalized recommendations and campaign automation within Wayfair's advertising platform. Your responsibilities will include designing and implementing intelligent budget, tROAS, and SKU recommendations, as well as simulation-driven decisioning to enhance advertiser outcomes and unlock substantial commercial value. In collaboration with cross-functional teams, you will lead the development of GenAI-powered creative optimization and automation to drive incremental ad revenue and improve supplier outcomes. Additionally, you will elevate technical standards by promoting best practices in ML system design and development across the team. The ideal candidate for this role possesses a Bachelor's or Masters degree in Computer Science, Mathematics, Statistics, or a related field, along with 9+ years of experience in building large-scale machine learning algorithms. You should have a strong theoretical understanding of statistical models and ML algorithms, proficiency in programming languages such as Python, and experience with relevant ML libraries like TensorFlow and PyTorch. Strategic thinking, customer-centric mindset, and a desire for creative problem-solving are essential qualities for success in this position. Additionally, you should be adept at influencing senior-level stakeholders, possess excellent communication skills, and demonstrate the ability to shape technical roadmaps through cross-functional partnerships. Nice-to-have qualifications include experience with GCP, Airflow, and containerization, as well as familiarity with Generative AI and agentic workflows. Knowledge of Bayesian Learning, Multi-armed Bandits, or Reinforcement Learning is also advantageous. By joining Wayfair, you will be part of a dynamic and innovative team that is dedicated to reinventing the way people shop for their homes. If you are looking for a fast-paced environment that offers continuous learning and growth opportunities, Wayfair may be the perfect place for you to advance your career.,

You will be joining Zupee, the largest online gaming company in India with a dominant presence in the Casual & Boardgame segment. At Zupee, we are dedicated to creating skill-based games that bring joy to people's lives, entertain them, and provide opportunities to earn while playing. In our pursuit over the past three years, Zupee has been committed to enhancing people's learning abilities, skills, and cognitive aptitude through scientifically crafted gaming experiences. Our games offer a refreshing break from the daily stressors and aim to bring happiness into the lives of our players. As a Lead Data Scientist at Zupee, you will play a pivotal role in driving innovation in AI ML-based algorithms and personalized offer experiences. Your responsibilities will revolve around designing and implementing advanced machine learning models, particularly focusing on reinforcement learning techniques such as Contextual Bandits, Q-learning, SARSA, and more. By utilizing your expertise in classical ML and statistical methods, you will be instrumental in creating solutions that optimize pricing strategies, enhance customer value, and generate tangible business outcomes. To excel in this role, you should have a minimum of 6 years of experience in machine learning and at least 4 years in reinforcement learning, personalization, recommendation systems, pricing algorithms, pattern recognition, or artificial intelligence. Proficiency in classical ML techniques, including Personalization, Recommendation, Pricing, using algorithms like XGBoost, Deep Learning, and hands-on experience in RL methods such as Contextual Bandits, Q-learning, SARSA, and Bayesian approaches for pricing optimization is essential. Moreover, you should be adept at handling tabular data, proficient in Python and SQL, and have a strong grasp of ML frameworks like scikit-learn, TensorFlow, and PyTorch. Your key responsibilities will encompass developing cutting-edge ML models for dynamic pricing and personalized recommendations, applying RL techniques to solve pricing and optimization challenges, building AI-driven pricing agents, and collaborating closely with cross-functional teams to align solutions with strategic objectives. Additionally, you will be involved in designing and analyzing controlled experiments to validate the effectiveness of your models. Join Zupee as a Lead Data Scientist and be part of a dynamic team that is poised to make a significant impact in the gaming industry by leveraging AI and ML technologies to drive business growth and enhance user experiences.,