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Mogul & Co

AI/ML Full Stack Engineer (Mid Level)

Posted 13 Days Ago
Remote or Hybrid
2 Locations
110K-130K Annually
Mid level
Remote or Hybrid
2 Locations
110K-130K Annually
Mid level
The AI/ML Full Stack Engineer will design and maintain applications for predictive insights, develop data pipelines, implement ML models, and collaborate cross-functionally.
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Who We Are:

Winning today isn’t about spending more. It’s about knowing more. Understanding more. Seeing more. And acting sooner than everyone else.

Mogul & Co is The Media Intelligence Company — a combination of predictive technology, advanced analytics, and high-performance media acquisition designed to answer one question with clarity:

How does every $1 in media create the next $10 in revenue and business growth?

We are entering a pivotal phase, expanding rapidly with strong revenue growth. Our leadership integrates two worlds:

  • Silicon Valley hyper-growth operators with experience building frontier AI, automation, and data platforms.

  • Fortune 500 and agency executives who have managed global P&Ls, overseen billions in media investment, and led major transactions.

This blend shapes how we operate: focused, precise, data-driven, and oriented toward long-term value creation.

About the Role:

We’re seeking a AI/ML Full Stack Engineer to join the elite team scaling the technology behind our Predictive Intelligence platform. You’ll work at the intersection of machine learning, data engineering, and product development—creating the tools that allow clients to see weeks or months into the future with unprecedented accuracy. This is an excellent opportunity for an engineer looking to grow their AI/ML and full-stack skills in a high-impact environment

You will work across the full stack, from data ingestion and modeling to APIs and client-facing interfaces. This role goes beyond basic analytics or dashboarding. You will help design and productionize systems that integrate large-scale, real-time, multi-source data, apply predictive and causal modeling, and continuously learn from new signals.

This is an ideal role for an engineer who wants deep exposure to real-world AI systems, complex data environments, and mathematically grounded prediction at scale.

Key Responsibilities:

  • Design, build, and maintain full-stack applications that deliver predictive insights through scalable, user-facing interfaces

  • Develop and maintain automated data pipelines for ingesting, processing, and transforming large-scale structured and unstructured data

  • Implement, deploy, and maintain machine learning models including forecasting, regression, classification, and ensemble methods

  • Apply statistical and machine learning techniques to support forward-looking analysis and decision-making

  • Build and maintain backend services, APIs, and integrations that support analytics and modeling workflows

  • Support experimentation, testing, and validation of models and analytical outputs

  • Work with modern AI approaches, including large language models, to support automation and data-driven workflows

  • Optimize system performance, reliability, and scalability across data pipelines and ML services

  • Collaborate cross-functionally with engineering, product, and analytics teams to translate requirements into technical solutions

  • Contribute to best practices for code quality, monitoring, and operational stability of production ML systems

Required Qualifications:

  • Bachelor’s degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related quantitative field

  • 2–4 years of professional experience in software engineering with exposure to full-stack development

  • Strong proficiency in Python for data processing, modeling, and backend services

  • Experience with JavaScript/TypeScript and modern frontend frameworks such as React or similar

  • Hands-on experience building, training, evaluating, or deploying machine learning models in production or near-production environments

  • Solid grounding in statistics, probability, linear algebra, and predictive modeling concepts

  • Experience working with time-series data, forecasting, regression, or classification problems

  • Strong SQL skills and experience working with relational and/or analytical databases

  • Experience building and consuming REST or GraphQL APIs

  • Familiarity with cloud platforms such as AWS, GCP, or Azure and cloud-native architectures

  • Ability to reason about data quality, bias, model assumptions, and uncertainty

  • Strong problem-solving ability and comfort working in ambiguous, evolving technical environments

Preferred Qualifications:

  • Experience with advanced ML frameworks such as PyTorch, TensorFlow, or JAX

  • Exposure to probabilistic modeling, Bayesian methods, causal inference, or simulation-based approaches

  • Experience with large language models, embeddings, vector databases, or retrieval-augmented systems

  • Familiarity with data orchestration and pipeline tools such as Airflow, Dagster, or dbt

  • Experience working with streaming or near-real-time data pipelines

  • Knowledge of containerization and deployment using Docker and CI/CD workflows

  • Experience with observability and monitoring for ML systems

  • Background or strong interest in AdTech, MarTech, economics, or large-scale analytics systems

  • Understanding of experimentation frameworks, A/B testing, or model validation strategies

  • Master’s degree in a technical or quantitative field

Compensation:

  • Base Salary: $110k–$130k

  • Equity Grant with Quarterly Profit Participation

  • Aggressive Year-Round Bonus Program

Joining Now Means:

  • Higher Equity Ownership & Profit Participation

  • Accelerated Leadership Paths

  • Patents Contribution and Industry-Leading Innovation

  • Continued Perks, Benefits, Compensation that increase with hyper-growth

  • Chicago, New York, Los Angeles Offices

  • Big Company Operations, Startup Culture

Culture & Working Style:

We operate with the urgency of a startup and the discipline forged from over a decade of operations and growth:

  • Move fast with precision

  • High collaboration across technical and commercial teams

  • Ownership mindset with real autonomy and accountability

  • Decisions grounded in data, testing, and measurable outcomes

  • Hybrid flexibility balanced with intentional in-person collaboration

If you thrive in environments where complexity is embraced, learning is constant, and your work directly shapes the product and business, you’ll fit right in.

Mogul & Co. believes that all persons are entitled to equal employment opportunity and prohibits any form of discrimination by its managers, employees, vendors or customers based on race, color, religion, creed, gender (including pregnancy status), sexual orientation, gender identity (which includes transgender and other gender non-conforming individuals), gender expression, hair expression, marital status, parental status, age, national origin, ancestry, disability, medical condition, genetic information, veteran or military status, citizenship status, or any other characteristic protected (herein referred to as “protected characteristics”) by applicable federal, state, or local laws.

Equal employment opportunity will be extended in all aspects of the employer-employee relationship, including, but not limited to, recruitment, hiring, training, promotion, transfer, demotion, compensation, benefits, layoff, and termination. In addition, Mogul & Co. will make reasonable accommodations to known physical or mental limitations of an otherwise qualified person with a disability, unless the accommodation would impose an undue hardship on the operation of our business.

Benefits & Perks:

  • Comprehensive medical, vision, dental, life, HSA, and disability benefits from day one of employment

  • Wellbeing programs include, but are not limited to primary care support, mental health services, pet wellness, and behavioral health

  • Unlimited PTO

  • Paid parental leave

  • 401(k) retirement plan

  • Company bonuses or sales commissions

  • Equity compensation

Compensation Range: $110K - $130K


#BI-Remote

Top Skills

AWS
Azure
GCP
GraphQL
JavaScript
Jax
Python
PyTorch
React
Rest
SQL
TensorFlow
Typescript

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