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Founding Machine Learning Engineer Jobs in Princeton Junction, NJ

Machine Learning Engineer

New York, NY · On-site

$150K - $195K/yr

As a Machine Learning Engineer at WireScreen, you will be working across our data systems to unlock the source of truth behind one of the world's economic powerhouses: China. This role is critical to ...

Pangram Labs is hiring for a strong junior Machine Learning Engineer. In this role, you will build software to support the machine learning development cycle from data generation, to training models ...

We are seeking a mid-level Machine Learning Engineer to help develop and scale RAG systems across the company. This is a hands-on, full-lifecycle ML role with a strong emphasis on retrieval models ...

Machine Learning Engineer

New York, NY · On-site

$205K - $235K/yr

The Opportunity Good Inside is seeking a Machine Learning Engineer to join our Engineering team. This is not a research or data science role - we're looking for a strong backend engineer who has ...

Machine Learning Engineer

New York, NY · On-site

$205K - $235K/yr

The Opportunity Good Inside is seeking a Machine Learning Engineer to join our Engineering team. This is not a research or data science role - we're looking for a strong backend engineer who has ...

As an Applied Machine Learning Engineer, you will serve as a vital bridge between cutting-edge AI research and practical, real-world applications. Your work will focus on developing, fine-tuning, and ...

Showing results 41-60

Founding Machine Learning Engineer information

See Princeton Junction, NJ salary details

$33.2K

$135.6K

$203.7K

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

As of Sep 3, 2026, the average yearly pay for founding machine learning engineer in Princeton Junction, NJ is $135,558.00, according to ZipRecruiter salary data. Most workers in this role earn between $106,900.00 and $163,200.00 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.

What are popular job titles related to Founding Machine Learning Engineer jobs in Princeton Junction, NJ?

For Founding Machine Learning Engineer jobs in Princeton Junction, NJ, the most frequently searched job titles are:

What cities near Princeton Junction, NJ are hiring for Founding Machine Learning Engineer jobs?

Cities near Princeton Junction, NJ with the most Founding Machine Learning Engineer job openings:

Sr. Lead Machine Learning Engineer

Capital One

New York, NY • On-site, Remote

Full-time

Re-posted 2 days ago


Capital One rating

7.8

Company rating: 7.8 out of 10

Based on 148 frontline employees who took The Breakroom Quiz

89th of 174 rated banks


Job description

Sr. Lead Machine Learning Engineer

As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You'll participate in the detailed technical design, development, and implementation of machine learning applications using existing and emerging technology platforms. You'll focus on machine learning architectural design, develop and review model and application code, and ensure high availability and performance of our machine learning applications. You'll have the opportunity to continuously learn and apply the latest innovations and best practices in machine learning engineering.

What You'll Do:

The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following:

  • Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams

  • Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation)

  • Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment

  • Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications

  • Retrain, maintain, and monitor models in production

  • Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale.

  • Construct optimized data pipelines to feed ML models

  • Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code

  • Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI

  • Use programming languages like Python, Scala, or Java

Basic Qualifications:

  • Bachelor's Degree

  • At least 8 years of experience designing and building data-intensive solutions using distributed computing (Internship experience does not apply)

  • At least 4 years of experience programming with Python, Scala, or Java

  • At least 3 years of experience building, scaling, and optimizing ML systems

  • At least 2 years of experience leading teams developing ML solutions

Preferred Qualifications:

  • Master's or Doctoral Degree in computer science, electrical engineering, mathematics, or a similar field

  • Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform

  • 4+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow

  • 3+ years of experience developing performant, resilient, and maintainable code

  • 3+ years of experience with data gathering and preparation for ML models

  • 3+ years of people management experience

  • ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents

  • 3+ years of experience building production-ready data pipelines that feed ML models

  • Ability to communicate complex technical concepts clearly to a variety of audiences

  • Experience leveraging interactive AI tooling to accelerate productivity, utilizing capabilities beyond basic code completion

Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.

The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked.

McLean, VA: $229,900 - $262,400 for Sr. Lead Machine Learning Engineer


New York, NY: $250,800 - $286,200 for Sr. Lead Machine Learning Engineer


Richmond, VA: $209,000 - $238,500 for Sr. Lead Machine Learning Engineer


San Francisco, CA: $250,800 - $286,200 for Sr. Lead Machine Learning Engineer








Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter.

This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.

Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at theCapital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.

This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.

If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.

For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com

Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site.

Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).


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