Machine Learning Engineer

Job Description

Point72 is seeking a Machine Learning Engineer to join their Compliance Product Development team in Stamford, CT. The team focuses on delivering best-in-class compliance and surveillance tools, evaluating technologies, and integrating data sources. The Machine Learning Engineer will play a critical role in building production-ready applications that support front office investment professionals, specializing in natural language processing (NLP) solutions.

What this role involves:

• Contributing to projects across various ML disciplines, including NLP, unstructured data analysis, predictive modeling, and classic machine learning.
• Working with sparse data and applying techniques to improve model accuracy and generalization.
• Utilizing SpaCy, Hugging Face Transformers, PyTorch, TensorFlow, and other NLP frameworks for model development.
• Implementing MLOps strategies, including model versioning, automated retraining, monitoring, and CI/CD pipelines for ML workflows.
• Conducting data evaluation, including data preprocessing, feature engineering, and model performance assessment.
• Collaborating cross-functionally with data engineers, software developers, and product teams to integrate models into production systems.
• Staying up to date with the latest advancements in NLP and machine learning, applying new techniques as needed.

Requirements:

• 5+ years of experience in machine learning and NLP.
• Experience working in a Linux environment.
• Strong proficiency in Python and experience with ML frameworks such as PyTorch, TensorFlow, and Scikit-learn.
• Hands-on experience with SpaCy, Hugging Face, and Transformers for NLP applications.
• Expertise in working with sparse data and applying techniques such as data augmentation, weak supervision, and semi-supervised learning.
• Experience deploying and managing ML models in cloud-based environments (e.g. AWS SageMaker).
• Strong understanding of MLOps principles, including automated model retraining, performance monitoring, and infrastructure scaling.
• Experience with data evaluation techniques, model explainability, and error analysis.
• Solid grasp of NLP concepts, including tokenization, embeddings, attention mechanisms, and transformer-based architectures.
• Experience fine-tuning large-scale NLP models and LLMs.
• Familiarity with knowledge graphs and graph-based NLP techniques.
• Background in unsupervised learning or self-supervised learning for NLP.
• Commitment to the highest ethical standards.

What Point72 offers:

• Fully-paid health care benefits
• Generous parental and family leave policies
• Volunteer opportunities
• Support for employee-led affinity groups
• Mental and physical wellness programs
• Tuition assistance
• A 401(k) savings program with an employer match and more