Media Mogul · 6 hours ago
AI/ML Full Stack Engineer (Mid Level)
New York, NY
Full-time
Hybrid
Entry, Mid Level
$110K/yr - $130K/yr
2+ years expMogul & Co is The Media Intelligence Company specializing in predictive technology and advanced analytics. They are seeking an AI/ML Full Stack Engineer to scale their Predictive Intelligence platform, focusing on machine learning, data engineering, and product development to create tools for accurate future insights.
Marketing & Advertising
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
Qualification
Required
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
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
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
Company
Media Mogul
Media Mogul delivers strategic, integrated solutions across a diverse range of services, designed to elevate your brand and maximize your return on investment.
11-50 employees
Funding
Current Stage
Early StageCompany data provided by crunchbase