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Internship Machine Learning Compiler Engineer Jobs in New York

Visible Hands

Machine Learning Engineer

Manhattan, NY · On-site

$150 - $190/hr

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 ...

Trading Interview

Machine Learning Engineer

Manhattan, NY · On-site

$180 - $240/hr

We are looking for an engineer with robust experience in machine learning and strong mathematical foundations to join our growing ML team and to help drive the direction of our ML platform. Machine ...

New

Root Access, Inc.

Machine Learning Engineer

Manhattan, NY · On-site

$140 - $190/hr

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 ...

Root Access Inc

Machine Learning Engineer

New York, NY · On-site

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 ...

Capital One

Lead Machine Learning Engineer (IC)

New York, NY · On-site +1

$112K - $147K/yr

Lead Machine Learning Engineer (IC) As a Capital One Machine Learning Engineer (MLE), you'll be ... Internship experience does not apply) * At least 4 years of experience programming with Python ...

Capital One

Lead Machine Learning Engineer (IC)

New York, NY · On-site

$112K - $147K/yr

Lead Machine Learning Engineer (IC) As a Capital One Machine Learning Engineer (MLE), you'll be ... Internship experience does not apply) * At least 4 years of experience programming with Python ...

Capital One

Sr. Lead Machine Learning Engineer

New York, NY · On-site +1

$112K - $147K/yr

Sr. Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE) , you'll be ... Internship experience does not apply) * At least 4 years of experience programming with Python ...

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Internship Machine Learning Compiler Engineer information

What is the difference between Internship Machine Learning Compiler Engineer vs Internship Software Engineer?

AspectInternship Machine Learning Compiler EngineerInternship Software Engineer
FocusDeveloping and optimizing compilers for machine learning modelsDesigning, coding, and testing software applications across various domains
SkillsMachine learning, compiler design, programming (C++, Python)Programming, algorithms, software development
Work EnvironmentResearch labs, tech companies, AI-focused teamsTech companies, startups, software firms
Industry UsageAI, machine learning, deep learning industriesBroad software development across industries

Internship Machine Learning Compiler Engineers focus on creating and optimizing compilers for machine learning models, requiring knowledge of AI and compiler design. In contrast, Internship Software Engineers work on developing general software applications across various fields. Both roles involve programming skills but differ in their specialization and industry focus.

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The most popular types of Machine Learning Compiler Engineer jobs in New York are:

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Cities in New York with the most Internship Machine Learning Compiler Engineer job openings:

Internship Machine Learning Compiler Engineer jobs near you
Infographic showing various Internship Machine Learning Compiler Engineer job openings in New York as of August 2026, with employment types broken down into 1% As Needed, 75% Full Time, 23% Part Time, and 1% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution.

Machine Learning Engineer

Visible Hands

Manhattan, NY • On-site

$150 - $190/hr

Other

Posted 13 days ago

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).

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