Compliance, Machine Learning Engineer, Dallas, Vice President

Are you passionate about delivering mission-critical, high quality machine learning models, using cutting-edge technology,in a dynamic environment?

We are Compliance Engineering, a global team of more than 300 engineers and scientists who work 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 and to 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 firm is making a significant investment improve the precision/ recall of the Compliance models portfolio in 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 degree in 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.
• Experience in system design and evaluating the pros and cons of database choices, schema definition for data storage.
• Extensive experience with Machine Learning and Deep Learning toolkits (Tensorflow, PyTorch, Scikit-Learn, Hugging Face)

• Prior experience with LLMs and Prompt Engineering
• Prior experience in architecting/ deploying ML applications on AWS/ GCP
• Prior experience in code reviews/ architecture design for distributed systems.

We’re committed to finding reasonable accommodations for candidates with special needs or disabilities during our recruiting process. Learn more:

Goldman Sachs is an equal opportunity employer and does not discriminate on the basis of race, color, religion, sex, national origin, age, veterans status, disability, or any other characteristic protected by applicable law.

We offer a wide range of health and welfare programs that vary depending on office location. These generally include medical, dental, short-term disability, long-term disability, life, accidental death, labor accident and business travel accident insurance.

We offer competitive vacation policies based on employee level and office location. We promote time off from work to recharge by providing generous vacation entitlements and a minimum of three weeks expected vacation usage each year.

We assist employees in saving and planning for retirement, offer financial support for higher education, and provide a number of benefits to help employees prepare for the unexpected. We offer live financial education and content on a variety of topics to address the spectrum of employees’ priorities.

We offer a medical advocacy service for employees and family members facing critical health situations, and counseling and referral services through the Employee Assistance Program (EAP). We provide Global Medical, Security and Travel Assistance and a…