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Founding Machine Learning Engineer Jobs (NOW HIRING)

Clera

Founding Machine Learning Engineer

Mountain View, CA · On-site

$220K - $300K/yr

About the Role This is a founding-team ML engineering role at an early-stage AI data and services company, building core machine learning systems from scratch for frontier AI labs and enterprises.

New

Jobzhr

$180 - $280/hr

We're hiring our Founding Machine Learning Engineer (MLE) with expertise in Agent Development and Time-Series Modeling. You'll play a foundational role in building production-grade systems that ...

OneScreen

Founding Machine Learning Engineer

Boston, MA · On-site

About the role You'll be the founding ML engineer who owns our matching algorithms from exploration ... Real ranking and matching modeling fluency - learning-to-rank, retrieval and re-rank patterns, not ...

Photonium

Founding ML Engineer

Manhattan, NY · On-site

Photonium builds next-generation design software for optical systems, and they are seeking a Founding Machine Learning Engineer to design and implement their optical design agent. The role involves ...

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Founding Machine Learning Engineer information

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$31.5K

$128.8K

$193.5K

How much do founding machine learning engineer jobs pay per year?

As of Aug 25, 2026, the average yearly pay for founding machine learning engineer in the United States is $128,769.00, according to ZipRecruiter salary data. Most workers in this role earn between $101,500.00 and $155,000.00 per year, depending on experience, location, and employer.

What is a founding machine learning engineer?

A Founding Machine Learning Engineer is one of the first technical team members at a startup who specializes in designing, building, and deploying machine learning systems. This role involves working closely with the founders to set the technical direction, build core AI products, and establish best practices for data and model development. In addition to hands-on coding and experimentation, a Founding Machine Learning Engineer often influences product decisions and helps shape the company's engineering culture. The role typically requires a blend of deep technical expertise, startup agility, and a willingness to tackle both high-level strategy and low-level engineering tasks.

What are some unique challenges and expectations for a founding machine learning engineer in an early-stage startup?

As a Founding Machine Learning Engineer, you'll face the unique challenge of building the company's machine learning infrastructure from the ground up, often with limited resources and rapidly evolving requirements. You'll be expected to wear many hats, from designing and deploying models to setting up data pipelines and collaborating closely with product and engineering teams. Your role will also involve making critical decisions about technology stacks and best practices that will shape the company's technical direction. Additionally, you'll have significant influence on the company's culture and have ample opportunities for growth as the team expands.

What are the key skills and qualifications needed to thrive as a founding machine learning engineer, and why are they important?

To thrive as a Founding Machine Learning Engineer, you need deep expertise in machine learning algorithms, software engineering, and data science, often supported by a degree in computer science or a related field. Familiarity with tools such as Python, TensorFlow or PyTorch, cloud platforms, and experience deploying ML models in production are typically required. Strong problem-solving abilities, entrepreneurial mindset, and excellent communication skills set standout candidates apart. These skills and qualities are vital for driving innovation, building scalable solutions from scratch, and collaborating within a fast-paced startup environment.

Are founding machine learning engineers still in demand?

Founding machine learning engineers remain in high demand as companies seek to develop AI-driven products and services. They often require strong skills in deep learning, data modeling, and proficiency with tools like TensorFlow or PyTorch, with demand driven by growth in AI applications across industries.

How much does a founding machine learning engineer make?

A founding machine learning engineer typically earns between $100,000 and $180,000 annually, depending on experience, location, and company size. Equity and bonuses may also be part of the compensation package, especially in startup environments where they play a significant role in total earnings.
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Founding Machine Learning Engineer jobs near you
Infographic showing various Founding Machine Learning Engineer 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 $128,769 per year, or $61.9 per hour.

Founding Machine Learning Engineer

San Francisco, CA • On-site

Velvet
See more jobs at Velvetexternal

Full-time

Re-posted 8 days ago

Job description

Job Summary:
Velvet is a data research company focused on creating high-quality audiovisual training data for AI. They are seeking a Founding Machine Learning Engineer to build pipelines that convert raw footage into structured training data, managing the full lifecycle from processing scripts to deployment at scale.
Responsibilities:
• Build and enhance post-processing pipelines that clean, validate, and package large volumes of video and audio data for multimodal model training.
• Deploy and fine-tune open-source models for speech recognition, speaker diarization, video segmentation, and related tasks.
• Design infrastructure for large-scale distributed processing — parallelizing thousands of compute jobs across cloud platforms and optimizing for throughput and cost.
Qualifications:
Required:
• Strong experience in ML infrastructure, speech/audio processing, or large-scale data pipelines.
• Proficiency in PyTorch.
• Familiarity with distributed job orchestration.
• Claude Code pilled.
• A bias toward shipping. You default to building, not theorizing.
• Ability to work effectively in an early-stage environment where scope is broad and priorities shift fast.
Preferred:
• Prior work at a data company or frontier AI lab.
• Track record building pipelines that process tens of thousands of hours of audio or video.
• Experience with infrastructure cost optimization or model fine-tuning for production use.
Company:
Infra and data for interactive AI. Founded in 2025, the company is headquartered in San Francisco, US, , with a team of 2-10 employees. The company is currently Early Stage.

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