Staff Machine Learning Engineer

Описание

CloudX is building a new supply-side advertising platform for mobile publishers, with a long-term vision to be the simplest ad monetization platform using AI-native product experience.

Responsibilities

• Design, train, evaluate, and ship the models that power the revenue-optimization product
• Own the full lifecycle from feature definition through production deployment and online evaluation
• Make architectural calls regarding models, training frameworks, and serving approaches
• Write code to implement architectural decisions
• Work directly with Product and publishers to understand optimization needs and sequence the roadmap
• Lead by example to build out the ML discipline at CloudX, setting direction and raising the bar
• Help hire and mentor additional ML engineers as the function grows

Requirements

• Shipped ML into a production request path, serving real traffic under a latency SLO, where getting it wrong costs money
• Can discuss a specific system built, the lift measured, and how it was measured
• Owned the offline-to-online feature parity problem, understanding training/serving skew and having a view on consistency
• Run real experiments measuring real revenue impact, understanding the difference between model log-likelihood improvement and business revenue
• Comfortable outside Python and willing to learn enough Golang to read production serving code and contribute fixes
• Hands-on experience: regularly code and interested in continuing to do so
• Owned large projects end-to-end and know how to work well with others
• Strong written communication skills to articulate complex technical subject matter to engineers and non-engineers
• Early-stage mentality: grit, determination, good taste in trading off speed vs. perfection, knowing when to cut corners and when to advocate for rigor
• AI forward: actively experimenting with or using AI in software engineering practice to achieve great results
• High ownership: cares about work quality, customer problems, overall business, and contributing to success

Nice to have

• Adtech experience (SSP, DSP, ad exchange, RTB) or equivalent experience from other low-latency, revenue-objective ML domains (search ranking, recsys, marketplace pricing, quant execution)
• Auction and bidding model experience: hands-on experience with contextual bandits, reinforcement learning, Thompson sampling, or similar approaches
• Familiarity with RTB literature or systems like Meta’s Pearl
• Experience with AWS, ONNX, XGBoost, LightGBM, ClickHouse, Kubernetes for training orchestration, and Datadog for observability

We offer

• Annual US base salary range: $300,000+
• Meaningful founding-team equity
• Top-tier medical, dental, and vision benefits
• Generous hardware budget for computer, monitor, and other core equipment
• Flexible working hours, minimizing synchronous meetings
• No in-office requirement
• Remote work covering UTC-8 to UTC+6 time zones

Hiring process

• Compensation will be determined based on experience, qualifications, and location