Core Engineering, Machine Learning Engineer Vice President

The Core Engineering, Machine Learning Engineer, New York, Vice President

New York, NY, United States

The Core Engineering

The Core Engineering builds and operates the platforms, applications, data solutions, models, and analytics that power critical processes for The Core divisions of the firm (e.g., Risk, responsible for the risk profile of firm activities;
Controllers, responsible for the financial control and reporting obligations;
Compliance, responsible for the firm’s compliance, regulatory, and reputational risks;
Corporate Treasury, responsible for the firm’s liquidity, funding, balance sheet, etc.; and Human Capital Management, responsible for attracting, developing, and managing a global workforce). A centralized engineering structure in support of The Core enables a common platform model and operating framework that promotes consistent governance and scalable solutions, leveraging cloud, AI, and machine learning for innovation and efficiency. The Core Engineering’s 2,000+ engineers and strats deliver engineering, data, analytics, and quantitative capabilities within six business units:

Metrics & Analytics Platforms: responsible for the measurement and management of the firm’s risk, capital, and liquidity for The Core functions

The Core Strats: responsible for the development and implementation of models and other quantitative methodologies, including the accuracy and attribution of modeled metrics

Financials & Reporting: responsible for facilitating the production of the firm’s financials and a wide range of reporting functions

Non-Financial Risk & Controls: responsible for non-financial risk and control processes

Enterprise Platforms: responsible for platforms and applications that support critical operational processes across The Core such as payments, people processes, and procurement

Shared Services: responsible for driving the adoption of consistent engineering strategy, including data platforms, cloud, and AI enablement, as well as the management of technology risk

We are Compliance Engineering,a global team of more than 300engineers and scientists whowork on the most complex, mission-critical problems.

We:

• build and operate a suite of platforms and applications that prevent, detect, and mitigate regulatory and reputational risk across the firm.
• have access to the latest technology andto massive amounts of structured and unstructured data.
• leverage modern frameworks to build responsive and intuitive UX/UI and Big Data applications.

Within Compliance engineering, we are hiring for a Machine Learning Engineering role within Models Engineering. The firmis making a significant investment improve the precision/ recall of the Compliance models portfolioin 2024. To achieve that we are hiring experienced MLEs who have experience of developing and deploying ML models for big data in a distributed architecture.

As a member of our team, you will:

• Work with large scale structure and unstructured data. Drive end to end Machine Learning projects that have a high degree of scale and complexity
• Build infra for machine learning which involves feature engineering and scaling models to work at scale
• Develop, product ionize, and maintain ml models
• Run ML experiments by constantly tuning the features and the modeling approaches, documenting findings and results
• Collaborate closely with ML researchers, to accelerate the usage of cutting edge models
• Perform code reviews and ensure code quality

A successful candidate will possess the following attributes:

• A Bachelor's or Master's degreein Computer Science, or a similar field of study.
• 10+ years of hands‑on experience with building scalable machine learning systems
• Solid coding skills and strong Computer Science fundamentals (algorithms, data structures, software design)
• Expertise in Python & Py Spark
• Experience in working with distributed technologies like Scala, Pyspark, Iceberg, HDFS file formats (avro, parquet), AWS/ GCP, big data feature engineering.
• Ex…