Senior Software Engineer – Machine Learning, AI Labs

Senior Software Engineer – Machine Learning, AI Labs

Website blackrock BlackRock

We are a global investment manager helping more and more people

Job Description
About this role


The AI Labs team works collaboratively; and is a multi-disciplinary team with the following skills and capabilities: optimization, machine learning, statistical modeling, exploratory data analysis, natural language processing, data visualization, network/graph modeling, ETL, data pipelines, data architecture, communication, project / product management and strategy. We work with data from a wide variety of sources including text, news feeds, financial reports, time series transactions, user behavior logs, imagery, and real-time data.

AI Labs has offices in New York, Palo Alto, and Edinburgh. The team has several Stanford professors as senior advisors with world-class expertise in machine learning, statistics, optimization and stochastic control. These advisors include Emanuel Candes, Trevor Hastie, Robert Tibshirani, and Mykel Kochenderfer who dedicate time in our Palo Alto office and provide advice and mentorship for all members of the distributed team.


Your Responsibilities
Help lead architecture on a multi-discipline, multi-region team of data scientists, engineers, and investment professionals on a corporate-wide set of client, investor, and operational problems
Build and maintain tools and services supporting the full model development life cycle for statistical, ML, and optimization models (e.g., feature engineering, backtesting and simulation, validation, deployment)
Maintain and monitor production models and experimentation
Tune performance in both single-threaded and distributed environments
Enforce high-quality patterns and practices for maintaining model pipelines
You have
7+ years in software engineering, with 3+ years in API-backed ML deployment
Strong programming language skills in Python
Significant experience with SQL (e.g., RDBMS, Spark, Presto, or BigQuery)
Experience with modeling, optimization, and data manipulation tools (e.g., scikit-learn, XGBoost, cvxpy, Pandas, Spark, or PyTorch)
Experience with at least one low-level or scientific language (e.g., C, Rust, Go, Julia, or R)
*Bonus* Experience with data visualization technologies (e.g., Dash, streamlit, plotly, matplotlib, Superset, or other BI tools)

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