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Commission Machine Learning Startup Jobs in New York

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 ...

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 ...

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 ...

RESPONSIBILITIES This role involves developing software and machine learning algorithms for use in ... startup-stage company (founding engineer to Series A company). Must be able to successfully ...

Machine Learning Engineer

New York, NY · On-site

$160K - $250K/yr

This role involves developing software and machine learning algorithms for use in human computer ... startup-stage company (founding engineer to Series A company). Must be able to successfully ...

They are seeking Machine Learning Engineers to develop their platform for training, evaluating, and ... Preferred : • Open-source ML infra contributions. • Startup or frontier lab experience in fast ...

They are seeking Machine Learning Engineers to build a platform for training, evaluating, and ... Preferred : • Open-source ML infra contributions. • Startup or frontier lab experience in fast ...

WireScreen is a fast-growing Series A startup bringing clarity to one of the world's most complex ... As a Machine Learning Engineer at WireScreen, you will be working across our data systems to unlock ...

About the Role We are looking for a Machine Learning Engineer, MLOps to help operationalize and ... Great startup culture, including company off-sites * High-achieving team, including ex-Amazon ...

Bonus: * strong open-source portfolio * publications at top-tier ML venues * experience working in an early-stage startup environment * understanding of how machine learning models fail in the wild ...

Most importantly, we are a mission-oriented, high-growth startup and we are looking for folks that ... Design, develop, and productionize machine learning (ML) solutions in the fields of Document ...

Machine Learning Engineer

New York, NY · On-site

$150K - $195K/yr

WireScreen is a fast-growing Series A startup bringing clarity to one of the world's most complex ... As a Machine Learning Engineer at WireScreen, you will be working across our data systems to unlock ...

Senior Machine Learning Engineer

New York, NY · On-site

$114K - $157K/yr

About the Role We are looking for a Senior Machine Learning Engineer, MLOps to help operationalize ... Great startup culture, including company off-sites * High-achieving team, including ex-Amazon ...

Thrive in a high-impact, fast-paced, late-stage startup environment Your Expertise * 6+ years of professional experience building production machine-learning software systems * Proven experience ...

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Commission Machine Learning Startup information

What is the difference between Commission Machine Learning Startup vs Data Scientist?

AspectCommission Machine Learning StartupData Scientist
CredentialsDegree in Computer Science, Data Science, or related fields; experience with ML modelsDegree in Computer Science, Statistics, or related fields; proficiency in programming and data analysis
Work EnvironmentStartup setting, fast-paced, innovative projects, often remote or flexibleCorporate or research environment, collaborative teams, often office-based
Industry UsageTech startups, AI-focused companies, innovative product developmentTech firms, finance, healthcare, research institutions
Search & Comparison IntentUnderstanding roles in ML startups, freelance or commission-based opportunitiesCareer development, skill requirements, industry roles

Commission Machine Learning Startup roles focus on developing ML solutions within startup environments, often with flexible or freelance arrangements. Data Scientists typically work in established companies, applying statistical and programming skills to analyze data. Both roles require similar credentials but differ in work setting and industry focus.

What are the most commonly searched types of Machine Learning Startup jobs in New York?

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

What cities in New York are hiring for Commission Machine Learning Startup jobs?

Cities in New York with the most Commission Machine Learning Startup job openings:

Machine Learning Engineer

Visible Hands

Manhattan, NY • On-site

$150 - $190/hr

Other

Posted 19 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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