Research Engineer, Knowledge Graph Intelligence
Point72 is hiring a Research Engineer, Knowledge Graph Intelligence in New York, United States. It pays $175k-$250k a year and Level rates it ; you can apply on Point72.
Level's read on this job
- Level rates this role Builds AI ●●●●: the job is building AI systems.
- Tools and skills the posting cites include Hugging Face, PyTorch and Python.
- Level classifies it as a senior role.
- Level lists 199 other open roles at Point72.
AI in this role
Develop NLP and generative AI models and algorithmic solutions for compliance and surveillance intelligence.
A Career with point72’s Surveillance team
Point72’s Surveillance team sets the industry standard for intelligence-driven surveillance by proactively identifying, monitoring, and assessing various sources of compliance risk using proprietary tools and specialized tradecraft. We support senior management by providing strategic assessments, actionable recommendations, and real-time escalations. At Point72, members of the Surveillance team conduct integrated trade and communication surveillance and collaborate to turn information into intelligence for our internal customers. The team also monitors employee activity for evidence of violations of applicable federal securities laws, internal compliance policies and procedures, and relevant rules and regulations enforced by the SEC, FINRA, and other organizations.
What you’ll do
As a Machine Learning Engineer - Applied Scientist you will play a critical role in developing algorithmic solutions and models for production-ready applications that support our front office investment professionals. You will specialize in natural language processing (NLP) solutions that extract insights from unstructured text data, with additional capabilities in predictive modeling, clustering, and time series analysis. You will 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 NLP, while also conducting novel research as required. Specifically, you will:
- 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.
What’s REQUIRED
- 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.
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 https://point72.com/.
The annual base salary range for this role is $175,000-$250,000 (USD) , which does not include discretionary bonus compensation or our comprehensive benefits package. Actual compensation offered to the successful candidate may vary from posted hiring range based upon geographic location, work experience, education, and/or skill level, among other things.
How we rate this
Research Engineer, Knowledge Graph Intelligence at Point72 rates 90 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Questions you could be asked
- Walk me through fine-tuning a model: what data did you use, and how did you check the result?
- How do you decide that one model's output is better than another's for a given task?
- What NLP problem have you worked on, and how did you measure whether it actually worked?
- Tell me about a project where natural language processing was part of your work. What did you do?
- Tell me about a project where machine learning was part of your work. What did you do?
Adapt your resume
- List these exact terms on your resume: Fine-tuning, AI Evaluation, NLP, Natural Language Processing, and Machine learning. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.
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