Seeking a Machine Learning Engineer to apply AI technologies in high frequency trading, focusing on automation and collaboration with AI research.
About Cubist
Cubist Systematic Strategies, an affiliate of Point72, deploys systematic, computer-driven trading strategies across multiple liquid asset classes, including equities, futures and foreign exchange. The core of our effort is rigorous research into a wide range of market anomalies, fueled by our unparalleled access to a wide range of publicly available data sources.
Role/Responsibilities:
We are seeking a Machine Learning Engineer to join the High Frequency Trading Technology team.
This role will apply the latest AI technologies to solve various real-world problems and streamline day-to-day operations, such as creating a production support AI agent that helps monitor production problems and suggest actions.
This role will also work with the AI research group on various projects such as creating synthetic data for training and using MCP agents to streamline research workflow.
Requirements:
- PhD or PhD candidate in machine learning, computer science or other AI related research fields
- Experience with sequential modeling and time series forecasting using deep learning
- Experience with deep neural networks and representation learning
- Prior experience working in a data driven research environment
- Experience with translating mathematical models and algorithms into code
- Proficiency in programming languages such as Python and R
- Experience with machine learning software libraries such as TensorFlow or PyTorch
- Experience implementing Agent or Context engineering is strongly preferred
- Experience with natural language processing technology is strongly preferred
- Excellent analytical skills, with strong attention to detail
- Collaborative mindset with strong independent research ability
- Strong written and verbal communication skills
- Commitment to the highest ethical standards
Point72 New York, New York, USA Office
55 Hudson Yards , New York, United States, 10001
Similar Jobs
Financial Services
Lead MLOps engineering for recommendation systems: build distributed GPU training pipelines, real-time and batch serving, deploy quantized LLMs, manage vector databases, implement monitoring/observability, optimize performance and reliability, and collaborate with product and architecture teams to scale AI infrastructure in AWS.
Top Skills:
AwqAWSCudaDapoDockerEcsGpuGrpoKubernetesLlmsPtqPythonRayTransformer ModelsTrlVector DatabasesVerlVllm
Artificial Intelligence • Professional Services • Business Intelligence • Consulting • Cybersecurity • Generative AI
Design, build, and deploy scalable AI and ML solutions by wrangling and integrating data, implementing models (Python/Java, TensorFlow, Scikit-Learn), developing data pipelines and NLP applications, collaborating with clients, and mentoring junior team members to drive business insights and regulatory risk solutions.
Top Skills:
AWSDatabricksGCPJavaAzureNatural Language ProcessingPythonScikit-LearnSnowflakeTensorFlow
Artificial Intelligence • Professional Services • Business Intelligence • Consulting • Cybersecurity • Generative AI
Design, build, and deploy AI and machine learning solutions at scale. Develop data pipelines and scalable models, perform data wrangling and analysis, apply NLP and neural networks, collaborate with clients and teams, and contribute to open-source and iterative improvement of AI systems.
Top Skills:
AWSDatabricksGCPAzureNatural Language ProcessingNeural NetworksPythonScikit-LearnSnowflakeTensorFlow
What you need to know about the NYC Tech Scene
As the undisputed financial capital of the world, New York City is an epicenter of startup funding activity. The city has a thriving fintech scene and is a major player in verticals ranging from AI to biotech, cybersecurity and digital media. It also has universities like NYU, Columbia and Cornell Tech attracting students and researchers from across the globe, providing the ecosystem with a constant influx of world-class talent. And its East Coast location and three international airports make it a perfect spot for European companies establishing a foothold in the United States.
Key Facts About NYC Tech
- Number of Tech Workers: 549,200; 6% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Capgemini, Bloomberg, IBM, Spotify
- Key Industries: Artificial intelligence, Fintech
- Funding Landscape: $25.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Greycroft, Thrive Capital, Union Square Ventures, FirstMark Capital, Tiger Global Management, Tribeca Venture Partners, Insight Partners, Two Sigma Ventures
- Research Centers and Universities: Columbia University, New York University, Fordham University, CUNY, AI Now Institute, Flatiron Institute, C.N. Yang Institute for Theoretical Physics, NASA Space Radiation Laboratory
