Expression of Interest: Machine Learning Engineer

Moloco; New York (NY); On-site; USD 170,000 - 386,400; Full time

Benefits offered by this job

Medical, dental, and vision insurance

401(k) plan with company match

Flexible Time Off

Job summary

Moloco is seeking a Machine Learning Engineer in New York, NY, to design and deploy large-scale models for programmatic advertising. The role focuses on optimizing marketplace performance through advanced machine learning and offers collaboration with product and data teams. Candidates should have experience in production ML solutions and be proficient in Python and frameworks like TensorFlow or PyTorch. This position provides opportunities for technical leadership and innovation within a dynamic environment.

Qualifications

• 5–12+ years delivering ML solutions in high-stakes environments.
• Expertise in ranking, calibration, and multi-objective optimization.
• Experience with data pipelining and model architecture.

Responsibilities

• Design, train, and deploy large-scale ML models.
• Productionize and maintain scalable ML pipelines.
• Extract insights from datasets and define models.

Skills

Production ML at Scale

Algorithmic Mastery

Full-Lifecycle Engineering

Technical Versatility

Operational Stewardship

Technical Mentorship

Education

PhD or Master's degree in Computer Science or related field

Tools

Python

TensorFlow

PyTorch

SQL

Job description

About Moloco

Moloco builds some of the most powerful AI advertising solutions in the world. Our name—short for “machine learning company”—reflects our core mission: democratizing access to the advanced AI that has historically been reserved for tech giants. Led by machine learning pioneers who built some of the most successful ad systems at Google, including YouTube’s monetization engine and key search advertising technologies, we’re transforming how businesses grow and compete in the digital economy.

Built with AI from day one, Moloco’s planet‑scale machine learning platform powers a suite of solutions for advertising growth and monetization. Moloco Ads is an AI‑powered platform that delivers real business outcomes for mobile app marketers through performance‑based user acquisition. Moloco Commerce Media enables retailers and marketplaces to build revenue‑generating ad businesses that balance user experience and advertiser performance.

About The Role

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.

Key Responsibilities

• 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

• Production ML at Scale: 5‑12+ years 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: Strong foundation in ML and statistics applied to real‑world business challenges, with expertise in 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 deployment into online systems.
• Technical Versatility: Proficiency with modern ML toolkits (Python, SQL, TensorFlow or PyTorch) and data processing stacks (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, iterating based on real‑world feedback.
• Technical Mentorship: Passion for advancing the team’s collective bar by sharing best practices and guiding the technical direction of complex ML 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 navigating 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.

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, 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. 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.

Salary Ranges

• Region A: $200,000—$386,400 USD
• Region B: $180,000—$367,080 USD
• Region C: $170,000—$347,760 USD

Moloco Values

• Lead with Humility: Everyone’s voice is respected, valued, and heard. With humility, we become more open and accessible to each other. 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.

Equal Opportunity

Moloco is an equal‑opportunity employer. We highly value diversity in our current and future employees and do not discriminate (including in our hiring and promotion practices) on the basis of race, color, creed, religion, national origin, age, sex and gender, gender expression and identity, sexual orientation, marital status, ancestry, physical or mental disability, military or veteran status, or any other characteristic protected by law.

Candidate Privacy Notice

Your privacy matters to us. By applying, you acknowledge that you have reviewed our Candidate Privacy Notice.