Software Engineer, Machine Learning

This is a fully remote position, open to applicants in United States.

📋 Description

• Create and develop a robust marketing platform that effectively reaches the appropriate audience at any time and place.

• Construct high-volume services that maintain reliability even at scale.

• Design big data solutions utilizing open-source frameworks.

• Design, train, assess, and enhance models for deliverability, forecasting, and optimization.

• Refine thresholds, calibration, and guardrails to minimize false positives and decision-making noise.

• Establish offline and online evaluation workflows linked to measurable business outcomes.

• Collaborate with Product, Project Leads, and platform-oriented Machine Learning and Data Engineers to enhance service reliability, latency, observability, and data freshness.

• Share the responsibility for production systems, safely implement model enhancements, and engage in the on-call rotation.

• Transform data scientist prototypes into robust, scalable production systems.

• Oversee the deployment, monitoring, and maintenance of machine learning solutions that drive campaign optimizations at scale.

⛳️ Requirements

• Over 5 years of experience in building ML models that are deployed and operated in production environments.

• Exceptional proficiency in conveying technical concepts to non-technical stakeholders.

• Strong foundation in applied ML principles, including classification, regression, forecasting, and thorough evaluation.

• Comprehensive understanding of optimization within a business context.

• Proficient in Python and SQL, with a focus on production engineering disciplines such as testing, maintainability, and performance.

• Experience in balancing model quality, system limitations, and speed-to-production.

• Demonstrated experience in ownership and cross-functional collaboration.

• Background in ad tech, growth analytics, personalization, or performance marketing.

• Proficient in working with real-time or near-real-time data pipelines.

• Familiarity with experimentation frameworks and monitoring of production models.

• Experience with large-scale data processing and ML systems, including Kedro, AutoGluon, PyTorch, Polars, BigQuery/GCP, Airflow/SQLMesh, and Databricks ecosystems.

• Experience in Reinforcement Learning techniques such as Q-Learning or Multi-Armed Bandits is a plus.

🏝️ Benefits

• People-first company culture.

• Recognized as one of Ad Age’s Best Places To Work in 2026.

• Flexible remote work arrangement.