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Machine Learning Startup Jobs in New York (NOW HIRING)

Root Access Inc

Machine Learning Engineer

New York, NY · On-site

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 ...

Goodfire

Machine Learning Engineer

Manhattan, NY · On-site

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 ...

Goodfire

Machine Learning Engineer

Manhattan, NY · On-site

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 ...

exacare ai

Machine Learning Engineer

Manhattan, NY · On-site

They are seeking a Machine Learning Engineer focused on MLOps to operationalize and scale their ... moving, startup-style environment with a high degree of ownership Company : Exacare ai is the ...

exacare ai

Machine Learning Engineer

New York, NY · On-site

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 ...

SageSure

Senior Machine Learning Engineer

Jersey City, NJ · On-site

$127K - $168K/yr

... of a startup, we're hiring. SageSure, a leader in catastrophe-exposed property insurance, is ... As a Senior Machine Learning Engineer, you'll play a crucial role in optimizing orchestration ...

Chasm Select

Senior Machine Learning Engineer

Manhattan, NY · On-site +1

$150K - $180K/yr

ChasmTeam Senior Machine Learning Engineer at JudiHealth Location: Remote (For Non-Local) or Hybrid ... Most importantly, we are a mission-oriented, high-growth startup and we are looking for folks that ...

Chasm Select

Senior Machine Learning Engineer

Manhattan, NY · On-site

$150K - $180K/yr

Description ChasmTeam Senior Machine Learning Engineer at JudiHealth Location: Remote (For Non ... Most importantly, we are a mission-oriented, high-growth startup and we are looking for folks that ...

WireScreen

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 ...

exacare ai

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 ...

Attentive

Senior Machine Learning Engineer

New York, NY

$244K - $320K/yr

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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Machine Learning Startup information

See New York salary details

$27.9K

$46.6K

$96.3K

How much do machine learning startup jobs pay per year?

As of Aug 1, 2026, the average yearly pay for machine learning startup in New York is $46,588.00, according to ZipRecruiter salary data. Most workers in this role earn between $35,600.00 and $50,300.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive in the Machine Learning Startup position, and why are they important?

To succeed in a Machine Learning Startup, a strong background in computer science, statistics, and applied mathematics is essential, along with practical experience building and deploying machine learning models. Proficiency in tools such as Python, TensorFlow, PyTorch, and cloud-based platforms, as well as familiarity with data versioning and model deployment systems, is highly valuable. Adaptability, entrepreneurial thinking, and strong communication skills are crucial for thriving in the dynamic startup environment. These competencies enable effective product development, rapid iteration, and impactful collaboration within a fast-paced, resource-constrained setting.

What are the typical responsibilities and daily challenges when working at a Machine Learning Startup?

At a Machine Learning Startup, your daily tasks often include collecting and preprocessing data, training and validating models, collaborating with engineers to deploy solutions, and iterating rapidly based on feedback and performance metrics. You may also contribute to brainstorming sessions, product roadmapping, and customer discovery processes. Common challenges include working with limited labeled data, balancing research with production needs, and managing shifting priorities as the business pivots or scales. This dynamic environment provides a valuable opportunity to make a tangible impact, develop a broad skill set, and gain exposure to multiple aspects of both technology and entrepreneurship.

What is a Machine Learning Startup job?

A Machine Learning Startup job typically involves working in a fast-paced, early-stage company focused on developing and applying machine learning technologies. Employees may take on diverse responsibilities, including data collection, model development, algorithm optimization, and deployment. Since startups require adaptability, roles often blend research, engineering, and business-oriented problem-solving. These positions offer opportunities to work on cutting-edge innovations but may also demand long hours and rapid prototyping.

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 are popular job titles related to Machine Learning Startup jobs in New York? For Machine Learning Startup jobs in New York, the most frequently searched job titles are:
What job categories do people searching Machine Learning Startup jobs in New York look for? The top searched job categories for Machine Learning Startup jobs in New York are:
What cities in New York are hiring for Machine Learning Startup jobs? Cities in New York with the most Machine Learning Startup job openings:
Machine Learning Startup jobs near you
Infographic showing various Machine Learning Startup job openings in New York as of July 2026, with employment types broken down into 1% As Needed, 74% Full Time, 23% Part Time, 1% Temporary, and 1% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution, with an average salary of $46,588 per year, or $22.4 per hour.

Machine Learning Engineer

Root Access Inc

New York, NY • On-site

Full-time

Re-posted 22 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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