Senior / Staff Data & ML Engineer
Superscale
Software Engineering, Data Science
Posted on Mar 23, 2026
Senior / Staff Data & ML Engineer
Full-Time | Remote / Hybrid | Engineering
About the Role
We're building the intelligence layer behind Superscale — and we need someone who can turn raw data into an unfair advantage.
As our Senior/Staff Data & ML Engineer, you'll own the entire data stack: from building the warehouse that powers product and business decisions, to developing ML models that make our AI-generated ads outperform anything on the market. You'll work with a large proprietary dataset - the kind of moat most startups can only dream of.
This is a foundational hire. You'll shape how we collect, structure, and leverage data across the company — from product analytics and funnel insights to predictive models that help our customers win. If you're the kind of engineer who gets excited about building a data platform from near-zero and then using it to ship ML features that move revenue, this is your role.
We believe in hiring for breadth and building leverage through AI tooling. You'll be a full-spectrum engineer who uses coding agents and modern tooling to operate at 10x the output of a traditional team.
Key Responsibilities
Design and build our data warehouse from the ground up on top of cloud-native infrastructure, creating the single source of truth for product, marketing, and customer data
Architect data pipelines that capture the full picture: user funnels, product usage, AI agent performance, and campaign outcomes
Develop ML models that leverage our proprietary ad creative dataset to generate higher-performing assets — turning data volume into product quality
Build predictive systems that forecast ad campaign performance, not just individual asset metrics — helping customers allocate budget before they spend it
Integrate and analyze ad platform data from connected Meta and TikTok accounts to surface cross-platform insights that no single-platform tool can provide
Create robust data models and APIs that make insights accessible to the product team, AI agents, and end users
Establish data quality frameworks, monitoring, and observability so the team trusts the numbers
Collaborate closely with product and engineering to embed data and ML capabilities directly into the product experience
Evaluate and adopt modern data tooling (dbt, Airflow, Dagster, etc.) — picking what's right for our scale and trajectory, not what's trendy
Requirements
5+ years of experience in data engineering, with hands-on ML/data science work — you've built pipelines and trained models in production
Strong foundation in SQL, Python, and modern data stack tooling (warehouses, orchestration, transformation)
Experience designing data warehouses or lakehouses from scratch or near-scratch — you know how to make architectural decisions that scale
Proven ability to take ML models from prototype to production, including feature engineering, training, evaluation, and serving
Comfort with cloud infrastructure (AWS preferred) and containerized environments
Experience working with ad platform APIs and marketing/campaign data is a strong plus
You think in systems, not just scripts — you care about reliability, observability, and clean abstractions
AI-native working style: you actively use LLMs, coding agents, and automation tools to amplify your output. We're building toward 10x coding agents per developer — you should be excited about that, not skeptical
Nice to Have
Experience with NLP or computer vision models applied to creative/ad content
Background in ad tech, martech, or performance marketing analytics
Familiarity with real-time data processing and streaming architectures
Experience at an early-stage or high-growth startup where you had to build foundational systems
Contributions to open-source data or ML projects
What We Offer
Competitive salary and equity/stock options in a high-growth AI company
Flexible remote or hybrid work arrangement
Generous paid time off and company holidays
Professional development budget for conferences, courses, and certifications
Greenfield opportunity — you're not inheriting legacy systems, you're building the foundation
A team that values horizontal skill over narrow specialization, and invests in tooling that makes everyone more effective
Direct impact on product and business outcomes — your models will ship to customers
How to Apply
Please send your application to magnus@superscale.ai with your LinkedIn / GitHub profile and a short note on why this role excites you and what you'd build first.
We are an equal opportunity employer and welcome candidates of all backgrounds.