Engineering

Engineering

Machine Learning Engineer

Machine Learning Engineer

About BlueAlpha

BlueAlpha is rewriting how marketing technology is engineered. We're building an Al-native operating system where specialized agents handle optimizations across massive, heterogeneous datasets. This means unifying data pipelines, applied machine learning, and autonomous decision-making into a seamless system.

We challenge ideas, share openly, and strive for excellence without ego. If you want to push agentic Al beyond the lab and into production at scale, this is your chance.

Role Overview

As a Machine Learning Engineer at BlueAlpha, you'll own the modeling engine that powers our recommendations and agent workflows.

Your focus will be on Bayesian and time-series modeling for marketing effectiveness: building models that can answer, with appropriate uncertainty, what really drove performance and what needs to change in how channels, budgets, and strategies are set up.

You'll spend your time:

  • Designing and implementing Bayesian regression and time-series models.

  • Encoding priors and hierarchy so models reflect reality instead of just fitting noise.

  • Building evaluation and stability frameworks to ensure models are reliable across many customers and refresh cycles.

  • Turning those models into production-grade training and inference pipelines that other teams and agents can rely on.

You should be comfortable working with both point estimates and uncertainty, and focused on ensuring that models lead to clear, directional guidance on what to do next.

This is a high-leverage role: the quality of your models directly impacts how hundreds of millions of dollars get allocated.

Responsibilities

  • Design, develop, and maintain causal Bayesian and time-series models for marketing performance.

  • Define priors and modeling assumptions and document them clearly.

  • Build and own validation frameworks: train/test design, out-of-sample checks, and stability/robustness tests.

  • Integrate experimental results (e.g., geo holdouts, synthetic control) into long-term modeling frameworks.

  • Productionize models as reusable training and inference jobs, APIs, or batch exports.

  • Collaborate with Data Engineering and Forward Deployed Engineers on data pipelines, features, and diagnostics.

  • Monitor model health in production (fit, drift, stability) and drive iterative improvements.

Qualifications

Required

  • 4+ years in machine learning, data science, or applied statistics with real-world business data.

  • Strong Python skills (pandas/NumPy plus at least one of: scikit-learn, PyMC, Stan, NumPyro, TEP, Google-Meridian, etc.).

  • Solid foundation in statistics and probability (regression, uncertainty, hypothesis testing, causal reasoning).

  • Practical experience with time-series modeling (trends, seasonality, lags, forecasting).

  • Hands-on exposure to Bayesian modeling and a strong interest in deepening that expertise.

  • Proven experience deploying models to production (pipelines, scheduled jobs, or services) and working with SQL at scale.

  • Critical mindset toward model robustness, identifiability, and out-of-sample performance.

  • Comfort operating in a high-ownership, fast-paced startup environment.

Nice to Have

  • Experience with Marketing Mix Modeling (MMM), incrementality testing (geo-lift, synthetic control, BSTS-style models), or other marketing / growth measurement problems.

  • Deeper experience with probabilistic programming and Bayesian inference (e.g., MCMC, variational inference) in real projects.

  • Familiarity with modern data and ML tooling: Snowflake/BigQuery/Redshift, dbt, Airflow/Prefect, MLflow or similar platforms.

  • Experience building or consuming model APIs and integrating models into downstream applications, dashboards, or agent workflows.

  • Prior startup experience or work in environments where models directly inform high- stakes decisions (budget allocation, pricing, risk, supply/demand planning, etc.).

Compensation & Benefits

  • Compensation: competitive salary + meaningful equity — real ownership in BlueAlpha's success

  • Benefits: health insurance, flexible PTO, and remote-friendly work

  • Impact: work on multi-faceted problems end-to-end

  • Culture: A collaborative, high-energy environment where we challenge ideas, not people — small team, big ambition

How to Apply

Ready to help define the future of Al-driven marketing? Send your resume and a short note to careers@bluealpha.ai.

Your marketing is capable of more.
Get on BlueAlpha. Make it happen.

Your marketing is capable of more.
Get on BlueAlpha. Make it happen.

Your marketing is capable of more.
Get on BlueAlpha. Make it happen.