As a Machine Learning Engineer at Moloco, you will design, train, and deploy the large‐scale models that power our programmatic advertising and commerce media products. You will work at the heart of our real-time bidding and pricing systems, helping shape an end-to-end ML ecosystem that processes billions of daily events. Your work will directly improve marketplace performance for global advertisers and publishers by optimizing for relevance, ROI, and user experience at a scale few companies can match.
The Opportunity
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.
Expertise We Value:
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 bring a deep technical foundation in the following areas:
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.
Our Tech Stack:
Languages: Python, Go, C++
ML Frameworks: TensorFlow, PyTorch, JAX
Infrastructure: GCP, AWS, Kubernetes, Spark, BigQuery, BigTable
How You Work:
Your ethos is ownership
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 fall in love with the problem, not the solution
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.
You can apply for this role through our Open Positions page (or through our Internal Job Board if you are a current employee). We will review submissions on an ongoing basis.
Compensation & Benefits
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 Area
Region B: Seattle Office, Seattle, Los Angeles/Orange County, San Diego, Austin, Boston, Washington DC Metro Area, Miami
Region C: All other U.S. locations
Salary Ranges:
Moloco Thrive: Benefits and Well-Being:
We take care of you and create the conditions for you to do the best work of your career. Through a lens of inclusion, we offer innovative benefits that empower our employees to take care of themselves and their families so they can do the best work of their lives.
Moloco Values:
Lead with Humility: Everyone’s voice is respected, valued, and heard. With humility, we become more open and accessible to each other. 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 rigor and integrity. 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 mission and 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.
Additional Resources:
Moloco Company Blog
Moloco Leadership
Moloco Newsroom
AI Use in Interviews
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 before your interview to understand what to expect. Failure to comply with this policy may impact your candidacy.
Candidate Privacy Notice:
Your privacy matters to us. By applying, you acknowledge that you’ve reviewed our Candidate Privacy Notice.
