AI/ML Full Stack Engineer (Mid Level)

Mogul & Co. • Chicago, IL

6d

About The Position

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.

Requirements

• 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

Nice To Haves

• 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

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

Benefits

• 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

What This Job Offers

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