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Machine Learning Startup Jobs (NOW HIRING)

Goodfire

Machine Learning Engineer

San Francisco, CA · On-site

They are seeking a Machine Learning Engineer to contribute to the development of tools and ... Preferred : • Open-source ML infra contributions. • Startup or frontier lab experience in fast ...

EarnIn

Head of Machine Learning

Mountain View, CA · Hybrid

$477K - $583K/yr

... fast-paced startup environments. This leader should have a strong coding foundation, deep ... Define and own the machine learning roadmap in alignment with business goals. * Lead the ML ...

Tacit

Machine Learning Scientist

San Francisco, CA · On-site

$180 - $270/hr

About Tacit We are an early-stage, deep tech startup based in San Francisco, developing innovative ... As a Machine Learning Scientist, you will develop cutting‑edge AI models to integrate and decode ...

Steg.AI

Machine Learning Scientist

Irvine, CA · On-site

$140 - $200/hr

AI is a National Science Foundation (NSF) and investor-funded startup based in Orange County, California. Our machine learning team currently consists of 3 PhDs in Computer Vision.We are looking for ...

New

Neurable, INC

Machine Learning

Cambridge, MA · On-site

Company Description Neurable is a funded brain-computer interface (BCI) startup spun out of the ... We are currently looking for a Machine Learning Scientist/Researcher to join our team. We would ...

Neurable, INC

Machine Learning

Cambridge, MA

Company Description Neurable is a funded brain-computer interface (BCI) startup spun out of the ... We are currently looking for a Machine Learning Scientist/Researcher to join our team. We would ...

Abaka AI

Machine Learning Engineer

Mountain View, CA · On-site

They are seeking a Machine Learning Engineer to design and develop scalable training pipelines for ... paced startup environment, and able to demonstrate strong ownership and urgency in execution.

Abaka AI

Machine Learning Engineer

Mountain View, CA · On-site

The Machine Learning Engineer will design and develop scalable training pipelines for multimodal AI ... paced startup environment, and able to demonstrate strong ownership and urgency in execution.

OpenReq

Machine Learning Engineer

San Francisco, CA · On-site

Advex is a seed stage tech startup focused on solving challenges in computer vision through effective data collection. As a Machine Learning Engineer, you will shape the technical direction of the ...

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Machine Learning Startup information

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$25.5K

$42.6K

$88K

How much do machine learning startup jobs pay per year?

As of Aug 21, 2026, the average yearly pay for machine learning startup in the United States is $42,584.00, according to ZipRecruiter salary data. Most workers in this role earn between $32,500.00 and $46,000.00 per year, depending on experience, location, and employer.

What is a machine learning startup?

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 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 are the key skills and qualifications needed to thrive in a machine learning startup, 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.

More about Machine Learning Startup jobs

What cities are hiring for Machine Learning Startup jobs?

Cities with the most Machine Learning Startup job openings:

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

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What states have the most Machine Learning Startup jobs?

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Machine Learning Startup jobs near you
Infographic showing various Machine Learning Startup job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 75% Full Time, 23% Part Time, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $42,584 per year, or $20.5 per hour.

Machine Learning Engineer

Goodfire

San Francisco, CA • On-site

Full-time

Re-posted 19 days ago

Job description

Job Summary:
Goodfire is a research company focused on building safe and powerful AI systems. They are seeking a Machine Learning Engineer to contribute to the development of tools and infrastructure for interpretable AI systems, playing a key role in transforming research into usable product features.
Responsibilities:
• Turn cutting edge interpretability research into production ready tools.
• Optimize pipelines and infrastructure for frontier model interpretability, training, and inference.
• Integrate new machine learning workflows and pipelines into our product and deploy to customers.
• Ensure system reliability, reproducibility, and performance.
Qualifications:
Required:
• 5+ years of experience in ML infra, research engineering, or systems programming.
• Comfort working across research and engineering boundaries.
• Expertise in Python, PyTorch or Jax, and distributed systems.
• Experience deploying and maintaining ML systems at scale.
• You care about understanding how models work internally and using that to make them more reliable and useful in the real world.
Preferred:
• Open-source ML infra contributions.
• Startup or frontier lab experience in fast-moving teams.
Company:
Goodfire is an AI research lab using interpretability to turn AI into something that can be understood, debugged, and shaped like software Founded in 2024, the company is headquartered in San Francisco, USA, with a team of 11-50 employees. The company is currently Early Stage.

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