Staff Machine Learning Engineer

Who you are

• Bring 8-12 years of experience in applied machine learning or machine learning engineering, with a track record of shipping production models in ads, recommender systems, search, or large-scale ecommerce
• Apply deep hands-on expertise with modern ML toolchains (e.g., Python, PyTorch/TensorFlow/JAX, feature stores, distributed training, and large-scale data processing frameworks) to solve complex ranking and prediction problems
• Demonstrate experience building and optimizing models such as CTR predictors, retrieval models, conversion models, or recommendation systems, ideally including exposure to transformer-based architectures
• Navigate ambiguity by breaking loosely defined or novel business problems into well-structured ML projects, defining metrics, setting up experiments, and iterating based on data
• Collaborate effectively with cross-functional partners, tailoring complex technical concepts for non-technical stakeholders to drive alignment and decision-making across product, engineering, and go-to-market teams
• Lead as the most senior technical IC on a team, independently owning high-impact technical initiatives, influencing architecture and roadmap decisions, and setting a high bar for code quality and model performance
• Thrive in a fast-moving environment where combining rigorous experimentation with pragmatic engineering unlocks measurable value for advertisers, retailers, and end customers

What the job involves

• Design, build, and productionize core ML models for CTR prediction, retrieval, conversion, and search/recommendation that directly drive performance for Moloco Commerce Media customers
• Lead end-to-end experimentation cycles, from problem framing and offline modeling to online A/B testing and iteration, to continuously improve auction, ranking, and recommendation quality
• Partner closely with product, engineering, and solutions teams to translate retail media and ecommerce requirements into robust ML solutions, features, and evaluation frameworks
• Drive technical excellence across the ML stack by improving pipelines, model serving, and monitoring for low-latency, high-throughput, and highly reliable inference at scale
• Mentor and uplevel other machine learning engineers through design reviews, knowledge sharing, and best practices in modern ML and MLOps

Benefits

• Comprehensive health and wellness: Competitive health (100% coverage for you), dental, vision and life insurance for you and your family. In addition, enjoy membership to Calm, Headspace, Spring Health, as well as fitness and health reimbursements
• Professional development: $2,500 Learning and Development stipend annually to grow yourself professionally
• Food and snacks: Enjoy lunch on us. We bring lunch in for employees everyday, In addition, our kitchens are filled with healthy snacks and beverages for you to enjoy
• Paid parental leave: Our parental leave for primary and secondary caregivers have you covered when you welcome a new child into your family
• Unlimited vacation: We encourage team members to take time off to relax and recharge with our flexible paid time off policy. We also offer leave time for various reasons
• Financial benefits: We provide equity and generous retirement benefits that help you prepare for your future. In addition, home office setup and phone, internet and transportation reimbursements