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Internship Machine Learning Quant Jobs in New York

D. in Computer Science, Mathematics, EE, Physics, or a related quantitative field with a focus on Scientific Machine Learning (SciML). * Deep Learning Frameworks: 4+ years of expert-level experience ...

Machine Learning Researcher

New York, NY · On-site

$200K - $300K/yr

Virtu is a quantitative trading firm that uses cutting-edge models and infrastructure to provide liquidity to the global markets. As a Machine Learning Researcher at Virtu, you'll pursue high-impact ...

Virtu is a quantitative trading firm that uses cutting-edge models and infrastructure to provide liquidity to the global markets. As a Machine Learning Researcher at Virtu, you'll pursue high-impact ...

Machine Learning Engineer

New York, NY · On-site +1

$209K - $250K/yr

Master's degree in Computer Science, Statistics, Data Science, or related quantitative field plus ... Machine Learning (ML) and artificial intelligence (Al) tools Data Preprocessing, Exploration and ...

Machine Learning Engineer

New York, NY · On-site

$200K - $300K/yr

Virtu's Research Technology team is looking for an experienced Machine Learning Engineer to join a ... You will work closely with quants and engineers alike and will play a central role in shaping how ...

Virtu's Research Technology team is looking for an experienced Machine Learning Engineer to join a ... You will work closely with quants and engineers alike and will play a central role in shaping how ...

You'll spend the bulk of your internship working closely with full-time machine learning researchers on projects drawn from their own work. You might conduct an end-to-end study of an unexplored ...

You'll spend the bulk of your internship working closely with full-time machine learning researchers on projects drawn from their own work. You might conduct an end-to-end study of an unexplored ...

... machine learning methods, a broad range of public and proprietary data sources, and unparalleled computing power. We are looking for exceptional students to join us as quantitative researcher interns ...

Showing results 21-40

Internship Machine Learning Quant information

What is the difference between Internship Machine Learning Quant vs Data Scientist Intern?

AspectInternship Machine Learning QuantData Scientist Intern
Required CredentialsStrong programming skills, basic finance knowledge, coursework in machine learningStatistics, programming, domain knowledge, coursework in data analysis
Work EnvironmentFinancial firms, hedge funds, quantitative trading teamsTech companies, startups, research labs
Industry UsageFinance, trading, quantitative researchTechnology, marketing, healthcare analytics
Common Search IntentInternship roles in finance with machine learning focusInternship roles in data science across industries

Internship Machine Learning Quant roles typically focus on applying machine learning techniques to financial data within trading and investment firms. Data Scientist Intern positions are broader, spanning various industries like tech and healthcare, emphasizing data analysis and modeling. While both require programming and analytical skills, the finance-specific knowledge is more critical for Machine Learning Quant internships.

What are the most commonly searched types of Machine Learning Quant jobs in New York? The most popular types of Machine Learning Quant jobs in New York are:
What cities in New York are hiring for Internship Machine Learning Quant jobs? Cities in New York with the most Internship Machine Learning Quant job openings:

Machine Learning Engineer

Root Access Inc

New York, NY • On-site

Full-time

Re-posted yesterday


Job description

About the company
Root Access is a frontier electronics company. We are a NYC-based startup funded by top investors. Our team is a passionate mix of engineers across electrical, firmware, software, and machine learning.
Core Responsibilities
  • Architect Physics Foundation Models: Design and train deep learning models.
  • Build the ECAD Data Pipeline: Develop high-performance asset pipelines to convert geometric, discrete, and multi-layer PCB files (ODB++, IPC-2581, STEP, Gerber) into continuous space data.
  • Multi-Modal Architecture Integration: Collaborate on connecting upstream Graph Neural Networks (GNNs) or LLMs mapping schematic topologies to downstream spatial physics engines.
  • Optimize for Real-Time Execution: Optimize training and inference pipelines on GPU clusters.

Required Technical Skills & Qualifications
  • Education: Master's or Ph.D. in Computer Science, Mathematics, EE, Physics, or a related quantitative field with a focus on Scientific Machine Learning (SciML).
  • Deep Learning Frameworks: 4+ years of expert-level experience with PyTorch or JAX.
  • SciML Expertise: Direct, hands-on experience building and training PINNs, FNOs, etc.
  • Mathematical Depth: Exceptional understanding of partial differential equations (PDEs), vector calculus, automatic differentiation (autograd), and numerical optimization algorithms (Adam, L-BFGS).
  • Data Pipelines: Strong proficiency in manipulating spatial or geometric datasets using Python libraries (NumPy, SciPy, Shapely, Open3D, or custom voxelization matrices).