Machine Learning Engineer
A CAREER WITH POINT72's COMPLIANCE PRODUCT DEVELOPMENT TEAM
As Point72 reimagines the future of regulatory technology, our Compliance Product Development team strives to deliver best in class compliance and surveillance tools in support of our Firm’s holistic surveillance program. Our work involves evaluating a broad range of technologies, doing custom development, and integrating with multiple upstream and downstream data sources and systems. We focus on innovation and excellence in a fast-paced, dynamic, and collaborative working environment.
What you’ll do
We are seeking a machine learning engineer who will play a critical role in building production-ready applications that support our front office investment professionals. We are interested in all aspects of ML including predictive modelling, clustering, time series analysis, and natural language processing. Successful engineers manage all aspects of the research process including methodology selection, data collection and analysis, implementation and testing, prototyping, and performance evaluation. You will apply, adapt, and extend existing results in the broad field of machine learning, while also conducting novel research as required.
- Contribute to projects across various ML disciplines, including Natural Language Processing (NLP), unstructured data analysis, predictive modeling, and classic machine learning.
- Work with sparse data and apply techniques to improve model accuracy and generalization.
- Utilize SpaCy, Hugging Face Transformers, PyTorch, TensorFlow, and other NLP frameworks for model development.
- Implement MLOps strategies, including model versioning, automated retraining, monitoring, and CI/CD pipelines for ML workflows.
- Conduct data evaluation, including data preprocessing, feature engineering, and model performance assessment.
- Collaborate cross-functionally with data engineers, software developers, and product teams to integrate models into production systems.
- Stay up to date with the latest advancements in NLP and machine learning, applying new techniques as needed.
What’s REQUIRED
- 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
We take care of our people
We invest in our people, their careers, their health, and their well-being. When you work here, we provide:
- Fully-paid health care benefits
- Generous parental and family leave policies
- Volunteer opportunities
- Support for employee-led affinity groups representing women, people of color and the LGBT+ community
- Mental and physical wellness programs
- Tuition assistance
- A 401(k) savings program with an employer match and more
About point72
Point72 is a leading global alternative investment firm led by Steven A. Cohen. Building on more than 30 years of investing experience, Point72 seeks to deliver superior returns for its investors through fundamental and systematic investing strategies across asset classes and geographies. We aim to attract and retain the industry’s brightest talent by cultivating an investor-led culture and committing to our people’s long-term growth. For more information, visit www.Point72.com/about
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