Compliance, Machine Learning Engineer, New York, Vice President (Machine Learning)

Location: New York, NY, United States

Salary: USD 130,000–250,000 per year

Company

hirify.global is a global investment banking, securities, and investment management firm with offices around the world.

What you will do

• Build and operate machine learning platforms and applications that prevent, detect, and mitigate regulatory and reputational risk.
• Lead end-to-end machine learning projects using large-scale structured and unstructured data.
• Build machine learning infrastructure, including feature engineering and model scaling for distributed environments.
• Develop, productionize, maintain, and continuously tune machine learning models.
• Collaborate with machine learning researchers to accelerate the use of advanced models.
• Conduct code reviews and maintain high standards of code quality and system design.

Requirements

• Bachelor’s or master’s degree in computer science or a related field.
• 10+ years of hands-on experience building scalable machine learning systems.
• Strong coding skills and computer science fundamentals, including algorithms, data structures, and software design.
• Expertise in Python and PySpark, with experience in Scala, Iceberg, HDFS file formats, AWS or GCP, and big data feature engineering.
• Experience with system design, database selection, and schema definition for data storage.
• Extensive experience with TensorFlow, PyTorch, Scikit-Learn, HuggingFace, and other machine learning and deep learning toolkits.

Nice to have

• Experience with LLMs and prompt engineering.
• Experience architecting and deploying machine learning applications on AWS or GCP.
• Experience with code reviews and architecture design for distributed systems.

Culture & Benefits

• Access to modern technology and large volumes of structured and unstructured data.
• Training and development opportunities and firmwide professional networks.
• Benefits, wellness, personal finance offerings, and mindfulness programs.
• Commitment to diversity, inclusion, and reasonable accommodations during the recruiting process.