Prodege LLC Logo

Prodege LLC

Staff Machine Learning Engineer

Posted 15 Days Ago
Be an Early Applicant
In-Office
El Segundo, CA, USA
240K-290K Annually
Senior level
In-Office
El Segundo, CA, USA
240K-290K Annually
Senior level
Build, deploy, and operate production ML systems (recommendation, ranking, personalization, optimization). Own feature engineering, training pipelines, online inference, experimentation, monitoring, retraining, and MLOps. Partner cross-functionally, mentor engineers, and deliver measurable business outcomes on a large-scale data platform.
The summary above was generated by AI

Job Description:

Read this part first:

This is a role for someone who wants to solve hard machine learning problems by building production systems that matter.

We're looking for a Staff Machine Learning Engineer who loves shipping production ML systems, owning complex technical problems end-to-end, and partnering closely with Product, Data Engineering, and the business to deliver measurable outcomes.

This is a deeply hands-on individual contributor role. You'll spend the majority of your time building, deploying, experimenting with, and improving production machine learning systems, not managing people or operating primarily at the architectural strategy level.

If you enjoy taking ownership of difficult ML problems, iterating quickly through experimentation, and seeing your work directly improve revenue, marketplace efficiency, and customer experience, this role is for you.

You'll build production ML systems for a business serving 120M+ registered users that has delivered $2B+ in lifetime rewards, powered by a data platform with 50M daily events, 500M daily pipeline records, a 100TB Iceberg lake, and 50 Kafka topics supporting both batch and real-time workflows.

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 Blackstone in Q1 2026, 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!

What you'll own
  • Design, build, and operate production machine learning systems from development through deployment

  • Production models supporting ranking, recommendations, personalization, rewards optimization, ROAS/LTV prediction, and offer optimization

  • Feature engineering, model training pipelines, online inference, experimentation, monitoring, and continuous improvement

  • Reliable production ML practices including testing, observability, retraining, and model health

  • Technical leadership through code reviews, collaboration, and mentoring less experienced engineers

  • Cross-functional partnerships with Product, Data Engineering, Analytics, and Business stakeholders to solve high-impact problems

What makes this role exciting
  • You'll work on machine learning problems that directly impact revenue, marketplace efficiency, and customer experience.

  • You'll own production systems—not just models—from experimentation through deployment and optimization.

  • You'll build on top of a production platform processing 50M daily events, 500M daily pipeline records, and a 100TB Iceberg lake.

  • You'll join a team with an active experimentation culture, shipping ML improvements that quickly reach production.

  • You'll have significant ownership while partnering with senior technical leaders to shape the future of ML at Prodege.

  • You'll work in an engineering culture embracing AI-assisted development to improve productivity and accelerate experimentation.

What you'll do
  • Design, build, deploy, and maintain production machine learning systems.

  • Develop scalable ML solutions across ranking, recommendation, personalization, rewards optimization, ROAS/LTV prediction, and experimentation.

  • Improve feature engineering, model performance, inference latency, and operational reliability.

  • Design and analyze offline evaluations and A/B experiments to validate business impact.

  • Partner with Data Engineering to build reliable data pipelines and feature sets for ML.

  • Contribute to MLOps practices including deployment, monitoring, retraining, and model lifecycle management.

  • Review code, mentor teammates, and help raise engineering quality across the ML organization.

  • Leverage AI-assisted development to accelerate research, prototyping, debugging, documentation, and experimentation.

What you'll bring (must-haves)
  • 6+ years of experience in Machine Learning Engineering, Software Engineering, MLOps, or related technical fields.

  • 3+ years building, deploying, and operating production machine learning systems.

  • Strong experience building production recommendation, ranking, personalization, optimization, or prediction systems.

  • Experience working in AdTech, MarTech, Growth, Consumer Products, Marketplace platforms, or adjacent domains.

  • Strong understanding of:

    • Feature engineering

    • Offline and online inference

    • Experimentation and A/B testing

    • Model serving

    • Monitoring and retraining

    • MLOps best practices

  • Experience partnering closely with Product, Engineering, and Data teams to deliver measurable business outcomes.

  • Strong software engineering fundamentals with excellent coding skills.

  • Comfort operating in ambiguous environments while independently driving technical solutions.

  • Demonstrated ability to mentor engineers and influence technical decisions across teams.

Bonus points
  • Experience with ROAS optimization, bidding systems, rewards platforms, or monetization models.

  • Experience with streaming or near-real-time ML systems.

  • Experience with recommendation engines or personalization at scale.

  • Experience using feature stores or shared ML infrastructure.

  • Experience with causal inference, uplift modeling, or counterfactual reasoning.

  • Master's degree or PhD in Machine Learning, AI, Computer Science, or a quantitative discipline.

  • Experience using AI-assisted development tools in software engineering workflows.

    Pay Transparency:

    The anticipated base salary range for this position is $240,000 to $290,000. The final salary offered to a successful candidate will be dependent on several factors that may include, but are not limited to; the type and length of experience within the job, type and length of experience within the industry, the type and length of knowledge and skills for the position, education, training, etc. Prodege is a multi-state employer and final compensation within this range could be impacted by work location. Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits.


    Prodege 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.


    Equal Employment Opportunity Statement

    At Prodege, we are committed to creating a diverse and inclusive environment. We are proud to be an Equal Opportunity Employer and do not discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, disability, veteran status, or any other characteristic protected by law. We encourage individuals of all backgrounds to apply.


    FCIHO

    Employers will consider for employment qualified applicants with criminal histories in a manner consistent with the requirements of FCIHO.


    HQ

    Prodege LLC El Segundo, California, USA Office

    Prodege is located in the heart of El Segundo with easy access to freeways, LAX, great restaurants, and the beautiful beaches of the South Bay!

    Similar Jobs

    6 Days Ago
    Hybrid
    Senior level
    Senior level
    Artificial Intelligence • Cloud • HR Tech • Information Technology • Productivity • Software • Automation
    Design and productionize agentic AI systems and components, improve agent behavior and reliability, create eval benchmarks and high-quality datasets, tune and evaluate LLMs and models, optimize latency and reliability in production, and partner with platform and UI teams to deliver end-to-end ML solutions.
    Top Skills: Deep Learning ArchitecturesGoHybrid Vector DatabasesLlmsMultimodal Foundation ModelsPython
    6 Days Ago
    Remote or Hybrid
    185K-335K Annually
    Senior level
    185K-335K Annually
    Senior level
    Automotive • Big Data • Information Technology • Robotics • Software • Transportation • Manufacturing
    Technical lead for end-to-end ML and CV pipelines to reconstruct, validate, and maintain map primitives from multi-modal vehicle sensor data. Architect scalable offline and production map reconstruction systems, define technical strategy, drive cross-functional integration, mentor senior engineers, and ensure robustness, safety, and operational scalability for national-scale mapping.
    Top Skills: 3D PerceptionBev RepresentationsC++CameraComputer VisionDataset CurationLabeling WorkflowsLarge-Scale Ml Data PipelinesLidarMachine LearningModel Training And EvaluationMonitoringMulti-View GeometryProduction Ml DeploymentPythonRadarSimulation
    13 Days Ago
    Easy Apply
    Hybrid
    Easy Apply
    144K-248K Annually
    Senior level
    144K-248K Annually
    Senior level
    Fintech • Mobile • Software • Financial Services
    Design, build, and operationalize ML-based security and anomaly detection across large-scale telemetry. Own feature engineering, model training, evaluation, deployment, drift monitoring, and SOC feedback loops. Partner with SOC, threat intel, and fraud teams to reduce noise and improve detection coverage, and mentor engineers on applied ML and detection operations.
    Top Skills: Amazon S3Apache IcebergAthenaAws GlueAws LambdaAws SagemakerDatabricksDelta LakeEdrExperiment TrackingFeature StoresFlinkGoogle Cloud Storage (Gcs)Google Pub/SubIgaKafkaKinesisMitre Att&CkModel RegistriesNetwork Proxy LogsPamPandasPythonPyTorchScikit-LearnSnowflakeSparkSpark StreamingSQLSsoTensorFlow

    What you need to know about the Los Angeles Tech Scene

    Los Angeles is a global leader in entertainment, so it’s no surprise that many of the biggest players in streaming, digital media and game development call the city home. But the city boasts plenty of non-entertainment innovation as well, with tech companies spanning verticals like AI, fintech, e-commerce and biotech. With major universities like Caltech, UCLA, USC and the nearby UC Irvine, the city has a steady supply of top-flight tech and engineering talent — not counting the graduates flocking to Los Angeles from across the world to enjoy its beaches, culture and year-round temperate climate.

    Key Facts About Los Angeles Tech

    • Number of Tech Workers: 375,800; 5.5% of overall workforce (2024 CompTIA survey)
    • Major Tech Employers: Snap, Netflix, SpaceX, Disney, Google
    • Key Industries: Artificial intelligence, adtech, media, software, game development
    • Funding Landscape: $11.6 billion in venture capital funding in 2024 (Pitchbook)
    • Notable Investors: Strong Ventures, Fifth Wall, Upfront Ventures, Mucker Capital, Kittyhawk Ventures
    • Research Centers and Universities: California Institute of Technology, UCLA, University of Southern California, UC Irvine, Pepperdine, California Institute for Immunology and Immunotherapy, Center for Quantum Science and Engineering

    Sign up now Access later

    Create Free Account

    Please log in or sign up to report this job.

    Create Free Account