Staff AI Engineer

abra • Wheaton, IL

3d

About The Position

abra R&D is looking for a Staff AI Engineer to help build a next-generation agentic analytics platform, the first real-time database optimized for AI agents at scale.
We are looking for a Staff AI Engineer to lead the design of data-driven models and analytical systems powering agentic analytics. This role focuses on causal inference, time-series modeling, and large-scale data analysis, working on real-time, high-dimensional datasets.

Requirements

• 7–10+ years of experience in data science / applied ML / quantitative research
• PhD or M.Sc in Computer Science, Statistics, Mathematics, or related field
• Strong programming skills in Python
• Causal Inference (required experience with several of the following) Propensity Score Matching (PSM) Inverse Probability Weighting (IPW) Difference-in-Differences (DiD) Instrumental Variables (IV) Regression Discontinuity Design (RDD) Causal Forests / Double Machine Learning (DML)
• Time Series (required experience with several of the following) ARIMA / SARIMA State Space Models / Kalman Filters Prophet VAR (Vector Autoregression) LSTM / Temporal Deep Learning models Transformer-based time-series models Anomaly detection in time-series (e.g., STL decomposition, change point detection)
• Machine Learning & Data Stack Strong experience with scikit-learn, XGBoost, LightGBM
• Experience with deep learning frameworks (PyTorch or TensorFlow)
• Experience with data processing (Pandas, NumPy, Spark)
• Experience working with large-scale or real-time data systems

Nice To Haves

• Experience with causal inference in production systems
• Background in analytics platforms or data products
• Experience working with time-series + event-driven data
• Familiarity with LLM-based systems or agentic analytics
• Experience designing experimentation platforms (A/B testing, uplift modeling)

Responsibilities

• Design and implement causal inference models to understand and drive decision-making
• Develop time-series models for real-time analytics and forecasting
• Build machine learning models on large-scale, structured and unstructured data
• Define statistical methodologies for agentic analytics and decision systems
• Work closely with AI and engineering teams to integrate models into production systems
• Analyze complex datasets and extract actionable insights
• Design experiments, evaluation frameworks, and data-driven feedback loops
• Contribute to the overall data science strategy and architecture

What This Job Offers

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