Machine Learning Engineer

Prodege • El Segundo, CA

13d • $160,000 - $185,000

About The Position

Strategic Imperative: The Machine Learning Engineer designs, builds, and productionizes end-to-end AI/ML systems that measurably improve business outcomes. This role owns the technical lifecycle of models from data and features through deployment, monitoring, and continuous improvement. You will ship reliable, well-tested services that move KPIs in areas such as ranking, recommendations, yield optimization, fraud detection, and intelligent routing, while also contributing to emerging AI initiatives including LLMs and agentic systems. Prodege: A cutting-edge marketing and consumer insights platform, Prodege has charted a course of innovation in the evolving technology landscape by helping leading brands, marketers, and agencies uncover the answers to their business questions, acquire new customers, increase revenue, and drive brand loyalty & product adoption. Bolstered by a major investment by Great Hill Partners in Q4 2021 and strategic acquisitions of Pollfish, BitBurst & AdGate Media in 2022, Prodege looks forward to more growth and innovation to empower our partners to gather meaningful, rich insights and better market to their target audiences. As an organization, we go the extra mile to “Create Rewarding Moments” every day for our partners, consumers, and team. Come join us today!

Requirements

• Bachelor’s degree in Computer Science, Engineering, Mathematics, or related field, or equivalent experience.
• 3+ years of hands-on ML engineering experience delivering models to production.
• Strong Python and working SQL; solid software engineering fundamentals including testing, modular design, and version control.
• Experience with classical ML such as tree-based models, linear/logistic models, and model evaluation.
• Working knowledge of a deep learning framework such as PyTorch or TensorFlow.
• Experience building data and feature pipelines for training and inference.
• Experience deploying models via APIs, microservices, or batch/streaming systems.
• Demonstrated ability to improve models through iteration, tuning, or redesign.
• Clear written and verbal communication; ability to partner effectively across teams.

Nice To Haves

• Master’s degree or PhD in AI, Machine Learning, or a quantitative field.
• Experience with ranking or recommendation systems at scale.
• Experience with distributed computing frameworks such as Spark, Ray, or Flink.
• Cloud experience on AWS, Azure, or GCP plus MLOps tooling such as MLflow or model registries.
• Familiarity with Docker/Kubernetes.
• Exposure to LLM tooling including Hugging Face, embeddings, RAG, or agent frameworks.
• Additional languages such as Java, Scala, or Rust.

Responsibilities

• End-to-End ML Systems: Build automated, scalable workflows for data ingestion, feature engineering, training, evaluation, and inference.
• Feature Platforms: Develop and maintain high-quality feature stores for batch and real-time use cases.
• Production ML: Package and deploy models as APIs, microservices, or streaming/batch jobs in collaboration with software and data engineering.
• Monitoring and Experimentation: Implement telemetry, data drift detection, performance tracking, and A/B testing to ensure reliability and impact.
• Collaboration: Partner closely with Product, Data, and Engineering to translate business problems into measurable ML solutions.
• Engineering Excellence: Write clean, maintainable, testable code; participate in code reviews; follow strong CI/CD and version control practices.

Benefits

• Prodege offers a comprehensive benefits package to US Full-time employees including medical, dental, vision, STD, LTD and basic life insurance.
• Employees receive flexible PTO, as well as paid sick leave prorated based on hire date.
• US Employees have eight paid holidays throughout the calendar year.
• Employees receive an option to purchase shares of Company stock commensurate with their position, which vests over four years.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level