[Remote] Machine Learning Engineer, Knowledge Graph Intelligence

Note: The job is a remote job and is open to candidates in USA. Point72 is a leading global alternative investment firm that seeks to deliver superior returns through fundamental and systematic investing strategies. They are looking for a Machine Learning Engineer specializing in natural language processing to develop algorithmic solutions and models that support investment professionals, while collaborating with cross-functional teams to integrate these models into production systems.

Responsibilities

• Contribute to projects across various machine learning (ML) disciplines, including NLP, unstructured data analysis, predictive modeling, and classic machine learning
• Implement GenAI solutions, utilize ML infrastructure, and contribute to modeling, data preparation, optimization, and performance enhancements
• Work with sparse data and apply techniques to improve model accuracy and generalization
• 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 natural language processing and machine learning, applying new techniques as needed

Skills

• PhD, master's degree, or 4+ years of CS, CE, ML or related field experience
• 6+ years of experience building ML models and developing algorithms
• Strong proficiency in Python, and hands-on experience with NumPy, Hugging Face, PyTorch, and spaCy for NLP applications
• Prior experience in the domains of LLMs, foundation models, or large-scale deep learning systems, with a complete understanding of modern training, fine-tuning, quantization, and model evaluation
• Expertise in working with sparse data and applying techniques such as data augmentation, weak supervision, and semi-supervised learning
• Solid grasp of NLP concepts, including tokenization, embeddings, attention mechanisms, and transformer-based architectures
• Experience with data evaluation techniques, model explainability, and error analysis
• Experience working in a Linux environment
• Commitment to the highest ethical standards

Benefits

• 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

Company Overview

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