Prodege, LLC · 16 hours ago
Machine Learning Engineer
United States
Full-time
Remote
Mid Level
$160K/yr - $185K/yr
3+ years expProdege, LLC is a cutting-edge marketing and consumer insights platform that helps leading brands and agencies improve business outcomes. They are seeking a Machine Learning Engineer to design, build, and productionize end-to-end AI/ML systems, ensuring the reliability and impact of deployed models while collaborating closely with cross-functional teams.
Digital MediaE-CommerceBig DataCrypto & Web3AdvertisingAppsMarketingAnalyticsGift CardMarket ResearchMobileSearch EngineVirtual Currency
Responsibilities
Build automated, scalable workflows for data ingestion, feature engineering, training, evaluation, and inference
Develop and maintain high-quality feature stores for batch and real-time use cases
Package and deploy models as APIs, microservices, or streaming/batch jobs in collaboration with software and data engineering
Implement telemetry, data drift detection, performance tracking, and A/B testing to ensure reliability and impact
Partner closely with Product, Data, and Engineering to translate business problems into measurable ML solutions
Write clean, maintainable, testable code; participate in code reviews; follow strong CI/CD and version control practices
Design, validate, and scale ML models including classification, regression, ranking, recommendations, NLP, and optimization systems
Build and maintain end-to-end ML pipelines for training and inference in both batch and streaming environments
Run and analyze experiments to improve model performance and business outcomes
Own feature quality, consistency, and governance across products and services
Ensure features are reliable for both offline training and online inference
Partner with data engineering on feature pipeline reliability, freshness, and availability
Deploy models via RESTful APIs, containerized services, or scheduled jobs, with appropriate reliability safeguards
Work with software and data engineering to integrate models into production systems
Ensure deployments are reproducible, versioned, and compatible with CI/CD practices
Instrument production systems with comprehensive monitoring for data drift, latency, prediction quality, and business impact
Define success metrics and guardrails for model performance in production
Identify degradation, diagnose root causes, and implement fixes in a timely way
Collaborate with stakeholders to define success metrics, communicate progress, and manage risks transparently
Translate business requirements into technical ML deliverables
Align model design with product roadmaps and engineering constraints
Write well-structured, modular, and testable Python code
Participate in peer code reviews and uphold team standards
Document systems, assumptions, and design decisions clearly
Follow version control, testing, and deployment best practices
Build or integrate retrieval-augmented generation systems using embeddings and vector stores
Experiment with prompt design, evaluation frameworks, and fine-tuning where appropriate
Apply guardrails, monitoring, and safety controls to LLM-powered features
Mentor junior engineers when applicable
Share learnings, patterns, and reusable components across teams
Contribute to shared tooling and best practices
Qualification
Required
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
Preferred
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
Benefits
Medical
Dental
Vision
STD
LTD
Basic life insurance
Flexible PTO
Paid sick leave prorated based on hire date
Eight paid holidays throughout the calendar year
Option to purchase shares of Company stock commensurate with their position, which vests over four years
Company
Prodege, LLC
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.
501-1000 employees
H1B Sponsorship
Prodege, LLC has a track record of offering H1B sponsorships. Please note that this does not
guarantee sponsorship for this specific role. Below presents additional info for your
reference. (Data Powered by US Department of Labor)
Distribution of Different Job Fields Receiving Sponsorship
Represents job field similar to this job
Trends of Total Sponsorships
2025 (2)
2023 (4)
2022 (2)
2020 (5)
Funding
Current Stage
Late StageTotal Funding
$60MKey Investors
Great Hill PartnersTCV
2021-11-15Private Equity
2014-04-01Series A· $60M
2008-01-01Series Unknown
Leadership Team
Joe Picciano
President / Interim CEO
Angela Valley
SVP Revenue & Operations
Recent News
EIN Presswire
2026-02-04
Canada NewsWire
2025-10-30
GlobeNewswire News Room
2025-01-30
Company data provided by crunchbase