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Founding Machine Learning Engineer Jobs (NOW HIRING)

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 ...

Known

AI / ML Engineer

San Francisco, CA · On-site

$200K - $375K/yr

Known - Founding Machine Learning Engineer * San Francisco, CA (In-Person) * 200k-375k Cash + Equity Known is a matchmaker that talks to users and supports them like a friend. Our mission is to ...

Socket.dev

Machine Learning Engineer

Los Angeles, CA · On-site

Role Description Founding Data Scientist / Machine Learning Engineer We're looking for a highly ambitious Data Scientist to help build the predictive intelligence layer behind nowfluence. This is not ...

Forhyre

Machine Learning Engineer

New York, NY

We are looking for a Machine Learning Engineer to help us create artificial intelligence products. Machine Learning Engineer responsibilities include creating machine learning models and retraining ...

Compunnel

Machine Learning Engineer

Philadelphia, PA · On-site

JOB SUMMARY We are seeking a hands-on Machine Learning Engineer to design, build, evaluate, deploy, and maintain machine learning models in production environments. The ideal candidate will have ...

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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 Sep 15, 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 September 2026, with employment types broken down into 1% Internship, 1% As Needed, 74% Full Time, 22% Part Time, and 2% Contract. Highlights an 82% Physical, 2% Hybrid, and 16% Remote job distribution, with an average salary of $128,769 per year, or $61.9 per hour.

Founding Machine Learning Engineer

Boston, MA • On-site

Onescreen
See more jobs at Onescreenexternal

Full-time

Re-posted 2 days ago

Job description

Job Summary:
Onescreen is a modern platform for out-of-home advertising, focused on streamlining the planning, buying, and measuring of OOH campaigns. They are seeking a Founding Machine Learning Engineer to own the development of matching algorithms and the data platform that supports them, along with designing and shipping models that optimize OOH inventory rankings.
Responsibilities:
• Design and ship matching and ranking models for OOH inventory: candidate generation, re-ranking, geospatial-aware scoring.
• Own the data warehouse layer end to end: staging, marts, feature pipelines, freshness, lineage.
• Stand up offline and online evaluation infrastructure — measure the gap between them, don't assume it.
• Publish ranking and matching APIs for product surfaces, with latency and quality SLOs.
• Instrument model monitoring: drift detection, prediction distribution, feature freshness, retraining triggers.
Qualifications:
Required:
• you have owned a production ranking, matching, or recommendation system end-to-end
• Strong production Python (NumPy, Pandas, FastAPI, SQLAlchemy)
• Strong SQL and modern data warehouse experience (BigQuery preferred)
• Real ranking and matching modeling fluency — learning-to-rank, retrieval and re-rank patterns, not just classification
• Evaluation methodology rigor: holdouts, leakage prevention, online vs. offline gap measurement
• Comfort owning the data pipeline as well as the model
• Bias toward shipping. Clear writer. Self-directed.
Preferred:
• Geospatial data experience (H3, PostGIS, GeoPandas)
• Mobility or location data experience
• Embedding-based retrieval (pgvector, FAISS, vector databases)
• Bandits, contextual bandits, or online learning
• A/B testing infrastructure design
• Causal inference
• dbt
• Ad-tech or OOH domain familiarity
Company:
Onescreen is the modern partner for out-of-home advertising. Founded in 2020, the company is headquartered in Boston, USA, with a team of 51-200 employees. The company is currently Growth Stage.

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