Prodege LLC Logo

Prodege LLC

Principal ML Engineer

Posted 20 Days Ago
Remote
Hiring Remotely in USA
300K-375K Annually
Senior level
Remote
Hiring Remotely in USA
300K-375K Annually
Senior level
Lead design, build, and operation of end-to-end production ML systems (feature pipelines, training, inference, experimentation, monitoring) for ranking, recommendation, rewards, ROAS/LTV prediction, personalization, and offer optimization in a high-scale AdTech environment. Provide hands-on technical leadership, mentor engineers, drive MLOps and observability standards, and partner with Data Engineering, BI, Product, and business teams to connect models to outcomes.
The summary above was generated by AI

Job Description:

Read this part first:

This is a role for someone who wants to own more than models. We're looking for a Principal Machine Learning Engineer to shape the future of machine learning across Prodege's Performance Marketing business, and this is a deeply hands-on principal role: you lead by building, shipping, and operating production ML systems, not by staying at the architecture or strategy layer.

If you want to hand designs to a team and review from a distance, this isn't your role, and that's okay. But if you're the kind of engineer who owns the ML stack end to end—from problem framing and feature strategy through model development, experimentation, deployment, observability, and lifecycle optimization—and wants your work to move revenue, margin, user value, and marketplace efficiency in a fast-moving AdTech / MarTech environment, keep reading.

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 events per day, 500M records of daily pipeline throughput, a 100TB Iceberg lake, and 50 Kafka topics and growing across batch and real-time workflows. If you enjoy building real-world ML systems, working close to the business, and helping a team move toward a more AI-first engineering model, this role is for you.

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:

    •    The architecture and delivery of offline / online ML systems, feature pipelines, inference patterns, feedback loops, and monitoring

    •    End-to-end ML systems spanning feature generation, training, inference, experimentation, monitoring, and lifecycle management

    •    Production ML algorithms and decisioning systems across ranking, rewards, ROAS / LTV, personalization, and offer optimization

    •    Experimentation frameworks that connect model performance to business outcomes

    •    Production-grade standards across MLOps, observability, retraining, governance, and reliability

    •    Hands-on technical leadership for the ML team through direct contribution, code reviews, and mentoring

    •    The evolution of ML toward a more AI-first way of working

What makes this role exciting:

    •    You'll directly shape how machine learning drives revenue, margin, and user value

    •    You'll work on analytically complex problems across ranking, rewards, ROAS, LTV, personalization, and optimization in a high-scale AdTech / MarTech environment

    •    You'll own ML from system design through production outcome, not just model development

    •    You'll build on top of a real production data platform operating at scale: 50M daily events, 500M daily pipeline records, a 100TB Iceberg lake, and 50 Kafka topics and growing

    •    You'll inherit a strong experimentation culture with 30+ ML experiments per month, 10 live experiments already this year, and a feature-rich data foundation with 1,000+ features, including user and item embeddings

    •    You'll build on real business momentum — our best ranking models are already outperforming the prior models

    •    You'll have principal-level scope to influence both the systems being built and how the broader ML organization works

    •    You'll help push the organization toward a more AI-first engineering future

What you'll do:

    •    Lead the design, build, and evolution of production ML algorithms and systems that drive real business outcomes

    •    Personally drive critical implementations, proving out new approaches in production before scaling them across the team

    •    Architect and ship scalable ML systems across offline training, online inference, feature pipelines, feedback loops, and model monitoring

    •    Build and evolve solutions across ranking and recommendation, rewards optimization, ROAS / LTV prediction, campaign and offer optimization, and experimentation and decisioning systems

    •    Establish robust experimentation and measurement frameworks, including offline evaluation, A/B testing, KPI design, and post-launch validation

    •    Make key decisions on MLOps, tooling, infrastructure, serving patterns, observability, and platform architecture

    •    Partner closely with Data Engineering, BI, Product, Engineering, and business teams to create reliable data foundations and connect ML work to business priorities

    •    Drive an AI-first mindset by using AI to accelerate research, prototyping, feature engineering, experiment analysis, debugging, documentation, and developer productivity

    •    Mentor ML engineers and data scientists by leading through direct contribution and raising the bar on model quality, technical judgment, and engineering rigor

What you'll bring (the must-haves):

    •    8+ years of experience in software engineering, machine learning engineering, MLOps, or related technical fields

    •    5+ years building, deploying, and supporting production ML systems at scale

    •    Strong experience in AdTech, MarTech, Growth, Performance Marketing, or adjacent domains

    •    Strong hands-on background in ranking, recommendation, rewards / incentives, ROAS / LTV prediction, and personalization / optimization systems

    •    Proven experience designing, shipping, and operating production ML systems end to end

    •    Strong understanding of offline / online ML architecture, feature engineering and feature platforms, model serving patterns, experimentation frameworks for ML systems, A/B testing and measurement design, and MLOps, retraining, monitoring, and governance

    •    Experience partnering closely with Data Engineering / BI / Analytics teams to create clean, scalable, and trustworthy data foundations for ML

    •    Strong system design skills with sound judgment across performance, reliability, scalability, and cost

    •    Ability to guide teams toward an AI-first way of working, while maintaining strong validation and engineering discipline

    •    Strong technical leadership and mentoring capability, with the ability to influence across teams without direct authority

    •    Comfort operating in ambiguity and still driving systems into production

Bonus points (the nice-to-haves):

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

    •    Experience in rewards, offer ecosystems, customer value optimization, or monetization platforms

    •    Experience with streaming or near-real-time decisioning systems

    •    Experience building ML platforms or shared experimentation infrastructure

    •    Master's degree or PhD in AI, Machine Learning, or a quantitative field

    •    Familiarity with modern AI-assisted / AI-first development practices across engineering and data science teams

Pay Transparency:

The anticipated base salary range for this position is $300,000 to $375,000. 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.


Similar Jobs

6 Days Ago
Remote or Hybrid
OH, USA
Expert/Leader
Expert/Leader
Financial Services
Lead design and delivery of scalable, secure AI/ML and cloud-based applications. Build reusable frameworks, produce production-quality code, advise cross-functional teams, mitigate technical risk, and influence senior stakeholders to drive platform and product outcomes.
Top Skills: Ai/MlApi GatewaysAWSAws BedrockAws Cloud DatabasesDynatraceKafkaObservability ToolsRelational DatabasesSaaSSalesforceSplunk
Yesterday
Remote or Hybrid
296K-424K Annually
Expert/Leader
296K-424K Annually
Expert/Leader
Automotive • Big Data • Information Technology • Robotics • Software • Transportation • Manufacturing
Lead technical vision and architecture for ML-driven trajectory generation in autonomous vehicles. Build and deploy scalable training pipelines, integrate models into real-time safety-critical onboard systems, mentor senior engineers, drive cross-functional initiatives, and move solutions from research to production using simulation and large-scale datasets.
Top Skills: C++Distributed Ml PipelinesGenerative ModelsImitation LearningLarge-Scale Training InfrastructureMotion PlanningOnboard Real-Time SystemsPythonReinforcement LearningSimulation EnvironmentsTrajectory Planning
12 Days Ago
In-Office or Remote
174K-274K Annually
Expert/Leader
174K-274K Annually
Expert/Leader
Cloud • Information Technology • Productivity • Security • Software • App development • Automation
Lead design and deployment of production-grade ML systems (ranking, retrieval, LLMs). Drive architecture decisions, run experiments and evaluations, build scalable feature pipelines and monitoring, mentor engineers, and collaborate cross-functionally to integrate AI into products and scale ML capabilities.
Top Skills: Feature EngineeringLlm-Based SystemsMl Model DeploymentModel EvaluationModel MonitoringOffline TrainingOnline InferenceRankingRetrieval

What you need to know about the Austin Tech Scene

Austin has a diverse and thriving tech ecosystem thanks to home-grown companies like Dell and major campuses for IBM, AMD and Apple. The state’s flagship university, the University of Texas at Austin, is known for its engineering school, and the city is known for its annual South by Southwest tech and media conference. Austin’s tech scene spans many verticals, but it’s particularly known for hardware, including semiconductors, as well as AI, biotechnology and cloud computing. And its food and music scene, low taxes and favorable climate has made the city a destination for tech workers from across the country.

Key Facts About Austin Tech

  • Number of Tech Workers: 180,500; 13.7% of overall workforce (2024 CompTIA survey)
  • Major Tech Employers: Dell, IBM, AMD, Apple, Alphabet
  • Key Industries: Artificial intelligence, hardware, cloud computing, software, healthtech
  • Funding Landscape: $4.5 billion in VC funding in 2024 (Pitchbook)
  • Notable Investors: Live Oak Ventures, Austin Ventures, Hinge Capital, Gigafund, KdT Ventures, Next Coast Ventures, Silverton Partners
  • Research Centers and Universities: University of Texas, Southwestern University, Texas State University, Center for Complex Quantum Systems, Oden Institute for Computational Engineering and Sciences, Texas Advanced Computing Center

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account