Expression of Interest: Machine Learning Engineer

About Moloco Moloco is an AI-native performance advertising company, bringing the power of AI advertising to the open internet. From the growing world of apps, connected TV, retail media, and wherever attention goes next, we deliver the measurable impact businesses need in the places where users are engaging the most. At Moloco, we combine advanced technology with hands-on expertise, from driving user acquisition and re-engagement for some of the world’s leading apps to powering the ad businesses of global retail giants. Customers share their business goals, and our compound AI system opens up new frontiers for performance. Moloco’s solutions reach over 200 countries and territories, and the company has offices throughout the US, the UK, Germany, Korea, China, India, Japan, and Singapore. Learn more at www.moloco.com.

Moloco

Bringing the power of AI advertising to the open internet

Machine LearningProgrammatic AdvertisingAdtechAdvertisingRetail MediaDSPDemand Side PlatformCommerce MediaAI advertisingPerformance Advertising

M

moloco.com

501-1,000 employees

Advertising Services

Menlo Park, California

2013

Privately Held

70k LinkedIn followers

• We know that for the most talented engineers, the right opportunity is about
• more than just a job title, it’s about the right challenge at the right time.
• Even if our current openings don't perfectly fit your timing and interests
• today, we still want to hear from you. We view this as a priority pathway to
• connect with curious, driven MLEs whose unique expertise can help us architect
• the next generation of planet-scale ML systems.
• At Moloco, our mission is to empower the global digital economy by turning
• massive first-party data into measurable business outcomes. Whether it’s
• optimizing real-time bidding for Moloco Ads or building AI-native stacks for
• Streaming and Commerce, we’re looking for engineers to help us lead the shift
• toward a more performance-driven, AI-powered internet.
• If you’re excited to scale and innovate in a fast-moving environment, share your
• profile and we will reach out the moment we see a potential match for your
• experiences and future goals.
• Architect and iterate on high-performance models that improve ad relevance,
• click-through rates, and conversion performance.
• Productionize and maintain scalable ML pipelines - from data ingestion to
• online inference - on top of planet-scale infrastructure.
• Extract insights from massive datasets of user behavior and auction signals
• to define new features and refine modeling strategies.
• Translate business goals (revenue, ROI, engagement) into concrete modeling
• challenges and success metrics in collaboration with Product and Data
• Science.
• Validate innovation through rigorous experimentation, including A/B tests,
• offline evaluations, and counterfactual analyses.
• Balance marketplace health by implementing models that harmonize advertiser
• value with a high-quality user experience.
• Enhance system reliability by refining feature stores, monitoring data
• quality, and establishing robust debugging practices.
• Drive platform evolution, contributing to ML tools and guidelines that
• increase experimentation velocity and deployment speed.
• Optimize for performance, partnering with Infra teams to reduce latency and
• improve throughput for low-cost, high-scale decisioning.
• Elevate technical excellence by sharing best practices in modeling and
• production ML with the broader engineering team.
• MLEs at Moloco are hands-on builders of some of the world’s highest-scale ML
• workloads. They bridge technical innovation with global revenue outcomes, owning
• the critical systems that define our next generation of machine learning and
• optimization platforms.
• While every journey is unique, we find that the most successful MLEs at Moloco
• Production ML at Scale: 5-12+ years of experience delivering ML solutions in
• high-stakes production environments (e.g., Ads, Recommenders, Search, or
• Marketplaces), with a track record of scaling models for massive throughput
• and low-latency requirements.
• Algorithmic Mastery: A strong foundation in ML and statistics applied to
• real-world business challenges, with expertise in areas such as ranking,
• calibration, exploration-exploitation, causal inference, or multi‑objective
• optimization.
• Full-Lifecycle Engineering: Deep understanding of the end-to-end ML
• lifecycle, including data pipelining, feature engineering, model
• architecture, inference optimization, and the deployment of models into
• online systems.
• Technical Versatility: Proficiency across a modern ML toolkit (Python, SQL,
• and frameworks like TensorFlow or PyTorch) and experience leveraging data
• processing stacks like Spark, Beam, or Flink to deliver results at scale.
• Operational Stewardship: Experience ensuring the long-term health of ML
• systems in live environments—monitoring performance, diagnosing drift, and
• iterating based on real-world feedback to maintain measurable impact.
• Technical Mentorship: A passion for advancing the team’s collective bar by
• sharing best practices for large-scale ML systems and guiding the technical
• direction of complex machine learning initiatives.
• Languages: Python, Go, C++
• ML Frameworks: TensorFlow, PyTorch, JAX
• Infrastructure: GCP, AWS, Kubernetes, Spark, BigQuery, BigTable
• You thrive in ambiguity and enjoy partnering with others to shape vague
• requirements into clear roadmaps with pragmatic tradeoffs.
• You take shared accountability for the end-to-end journey; communicating
• progress, surfacing risks early, and following through to ensure your work
• creates measurable value.
• You demonstrate strong judgment under uncertainty.
• You prioritize based on long-term impact, over short-term noise, making
• deliberate decisions when information is incomplete.
• You explicitly weigh tradeoffs like speed vs. quality and remain agile
• enough to adjust your approach thoughtfully as new information/data
• emerges.
• You lead through clarity and active listening.
• You reduce ambiguity for the team by asking the right questions upfront,
• tailor your communication to your audience, document your decisions, and
• bring helpful structure to complex discussions.
• You provide thoughtful, evidence-based feedback when needed and align
• behind decisions once they are made.
• You collaborate early, instead of solving in isolation.
• You build trust across the organization by listening first and navigate
• conflicting needs with empathy, creating buy-in around priorities and
• scope.
• You navigate technical tensions productively, disagreeing thoughtfully
• while maintaining momentum and strengthening professional relationships.
• You build for the long run, looking beyond immediate tasks to understand
• root causes, second-order effects, and the long-term health of our ML
• ecosystem.
• When something breaks, you don’t just patch it; you seek structural
• improvements that prevent recurrence and elevate the technical bar for the
• entire organization.
• You prioritize customer impact and take action to make it real.
• You prioritize effective solutions that drive business impact over
• technical elegance, spotting opportunities that others might overlook.
• You have the initiative to turn ideas into outcomes and the agency to
• identify and fix gaps, even when they aren’t yet on the formal roadmap.

• U.S.-based employees have access to medical, dental, and vision insurance, a
• 401(k) plan with company match, short-term and long-term disability coverage,
• basic life insurance, and well-being benefits and perks. U.S.-based employees
• also receive up to 12 scheduled paid holidays per calendar year and one Thrive
• Day off per quarter. Additionally, all employees have Flexible Time Off (FTO).
• The successful candidate may be eligible for a bonus and equity awards.
• Eligibility and amounts are determined by performance and the terms of the
• applicable plans.
• The location for this role is listed above. For base pay range purposes,
• location-based compensation is grouped into the following regions. Your region
• is determined by your assigned work location.
• Region A: Menlo Park Office, New York Office, SF Bay Area, New York Metro
• Region B: Seattle Office, Seattle, Los Angeles/Orange County, San Diego,
• Region C: All other U.S. locations
• Region A
• $200,000—$386,400 USD
• Region B
• $180,000—$367,080 USD
• Region C
• $170,000—$347,760 USD
• Our benefits are designed to support our people in doing their best work and
• living well, at work and beyond. Benefits vary by country, employment type, and
• eligibility. Connect with a recruiter to learn more about benefits in your
• region.
• Lead with Humility: Everyone’s voice is respected, valued, and heard. We win,
• lose, and learn together. Accountability and feedback are essential to our
• success.
• Uncapped Growth Mindset: We see all situations as opportunities to learn,
• grow, and improve as individuals and as an organization. We seek diverse
• perspectives, encourage curiosity, and promote experimentation to push the
• boundaries of what’s possible.
• Create Real Value: We pursue the most impactful opportunities with intensity
• and rigor. We take intelligent risks and make disciplined trade-offs to
• maintain deep focus. We help our customers win by delivering durable value.
• Go Further Together: We’re one team working towards one vision. We
• collaborate proactively and inclusively, involving the right people at the
• right time and in the right way. We strive to create a more equitable
• workplace. We won’t let each other fail.
• Moloco Company Blog [https://www.moloco.com/blogs]
• Moloco Leadership [https://www.moloco.com/company/leadership]
• Moloco Newsroom [https://www.moloco.com/newsroom]
• Our interview process is designed to get to know the real you. Unless a round
• specifically includes AI as part of what's being assessed, we ask that
• candidates engage without AI assistance. Please review our AI Use in Interviews
• Policy [https://www.moloco.cloud/hubfs/careers/AI%20Use%20in%20Interviews.pdf]
• before your interview to understand what to expect. Failure to comply with this
• policy may impact your candidacy.
• Your privacy matters to us. By applying, you acknowledge that you’ve reviewed