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Machine Learning Engineer Opt Jobs in Ridgefield Park, NJ

Canals

Machine Learning Engineer

New York, NY · On-site

We're looking for a senior-level Machine Learning Engineer who can move quickly while maintaining high quality, owning end-to-end ML pipelines while shaping product features that deliver real-world ...

Virtu Financial

Machine Learning Engineer

New York, NY · On-site

$200K - $300K/yr

Virtu's Research Technology team is looking for an experienced Machine Learning Engineer to join a small group of technologists whose primary function is building the infrastructure that powers our ...

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 scale our machine learning systems. This is an engineering-focused role centered on building the ...

Virtu Financial

Machine Learning Engineer

New York, NY · On-site

$200K - $300K/yr

Virtu's Research Technology team is looking for an experienced Machine Learning Engineer to join a small group of technologists whose primary function is building the infrastructure that powers our ...

Colgate-Palmolive

Machine Learning Engineer

Manhattan, NY · On-site

$105K - $150K/yr

Overview We are seeking a Machine Learning Engineer who brings the analytical rigor of a data scientist and the engineering discipline of a software architect. In support of Colgate-Palmolive ...

PROPRIUS

Senior Machine Learning Engineer

New York, NY · On-site

$114K - $157K/yr

Sr. Machine Learning Engineer Location: New York, NY Sponsorship: Yes Relocation: Yes Industry: Machine Learning A leading provider of AI is looking for a Sr. ML Engineer. Our client is an industry ...

RunSybil

Machine Learning Engineer

New York, NY · On-site

About this Role We are seeking talented engineers intent on changing the security industry. If you ... Understanding of both modern and classic machine learning techniques * Equally comfortable with ...

Namely

Machine Learning Engineer

Manhattan, NY · On-site

About the role We are seeking a Machine Learning Engineer to strengthen our element classification system - working closely with data scientists and data annotators to ship and improve entity ...

Teleskope

Machine Learning Engineer

New York, NY · On-site

$160K - $210K/yr

About the role We are seeking a Machine Learning Engineer to strengthen our element classification system - working closely with data scientists and data annotators to ship and improve entity ...

Errgo

Junior Machine Learning Engineer

Manhattan, NY · On-site

As a Junior Machine Learning Engineer, the candidate will contribute to building and deploying ML models that power intelligent features across the platform. This role offers the opportunity to work ...

Rapidtrade

Senior Machine Learning Engineer

Manhattan, NY · On-site

$115K - $158K/yr

About the Role We're looking for a Senior Machine Learning Engineer to join our AI team and help build the next generation of predictive trading models. You'll work on cutting-edge problems involving ...

Capital One

Sr. Lead Machine Learning Engineer

New York, NY · On-site +1

$112K - $147K/yr

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.

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All JobsMachine Learning Engineer Opt JobsMachine Learning Engineer Opt Jobs in Ridgefield Park, NJ

Machine Learning Engineer Opt information

See Ridgefield Park, NJ salary details

$33.8K

$138.2K

$207.7K

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

As of Sep 13, 2026, the average yearly pay for machine learning engineer opt in Ridgefield Park, NJ is $138,190.00, according to ZipRecruiter salary data. Most workers in this role earn between $108,900.00 and $166,300.00 per year, depending on experience, location, and employer.

What is a machine learning engineer?

Machine Learning Engineers are specialized software engineers who design, build, and deploy machine learning models into production environments. They work at the intersection of software engineering and data science, transforming data-driven prototypes into scalable, reliable systems that organizations can use to make predictions or automate tasks. Their responsibilities include data preprocessing, choosing appropriate algorithms, model training, and ensuring the model's performance in real-world applications. Machine Learning Engineers often collaborate with data scientists, data engineers, and product teams to deliver intelligent solutions.

What are some common challenges machine learning engineers face when deploying models to production environments?

Machine Learning Engineers often encounter challenges such as ensuring model scalability, handling data drift, and integrating models seamlessly with existing systems when deploying to production. Monitoring model performance in real time and retraining models as new data becomes available are also critical tasks. Collaboration with data engineers and DevOps teams is essential to address infrastructure and deployment hurdles while maintaining model accuracy and reliability.

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

To thrive as a Machine Learning Engineer, you need a solid background in mathematics, statistics, and programming (especially Python), typically supported by a degree in computer science, engineering, or a related field. Familiarity with machine learning frameworks (such as TensorFlow, PyTorch), data processing tools, and cloud platforms, along with relevant certifications, is highly valuable. Strong problem-solving ability, collaboration, and effective communication are standout soft skills in this role. These skills and qualities ensure the successful development, deployment, and integration of machine learning solutions that drive business value.

What is the difference between Machine Learning Engineer Opt vs Data Scientist?

AspectMachine Learning Engineer OptData Scientist
Required CredentialsBachelor's or Master's in CS, AI, or related fields; certifications in ML toolsBachelor's or Master's in CS, Statistics, or related fields; data analysis certifications
Work EnvironmentDevelops, tests, and deploys ML models in production systemsAnalyzes data, builds models, and provides insights for decision-making
Employer & Industry UsageTech companies, AI startups, e-commerce, financeResearch institutions, tech firms, consulting, finance
Common Search & ComparisonOften compared for technical skills and deployment focusCompared for data analysis and business insights

Machine Learning Engineers Opt focus on deploying scalable ML models in production environments, while Data Scientists primarily analyze data and develop models for insights. Both roles require strong technical skills, but their core responsibilities differ in application and deployment.

What are popular job titles related to Machine Learning Engineer Opt jobs in Ridgefield Park, NJ?

For Machine Learning Engineer Opt jobs in Ridgefield Park, NJ, the most frequently searched job titles are:

What cities near Ridgefield Park, NJ are hiring for Machine Learning Engineer Opt jobs?

Cities near Ridgefield Park, NJ with the most Machine Learning Engineer Opt job openings:

Machine Learning Engineer Opt jobs near you
Infographic showing various Machine Learning Engineer Opt job openings in Ridgefield Park, NJ as of August 2026, with employment types broken down into 17% Internship, and 83% Full Time. Highlights an 79% In-person, and 21% Remote job distribution, with an average salary of $138,190 per year, or $66.4 per hour.

Machine Learning Engineer

New York, NY • On-site

Canals
See more jobs at Canalsexternal

Full-time

Re-posted yesterday

Key responsibilities

  • Design, build, and maintain scalable machine learning models that improve and automate logistics processes for customers.

  • Own projects end-to-end, from problem definition and data exploration to model deployment and monitoring in production.

  • Collaborate closely with engineering teams to align ML work with customer needs and deliver features that drive business value.

Job description

About Canals
Canals builds software for wholesale distributors, helping them operate more efficiently through automation and AI.
Our customers are the companies responsible for moving the materials that power the real economy; electrical supplies, plumbing products, roofing materials, HVAC equipment, and more. Every day, thousands of people rely on Canals to help process orders, manage purchasing, handle accounts payable, and streamline critical business workflows.
We're a profitable, rapidly growing company with a team of roughly 100 people distributed across North and South America. We care deeply about building great products, hiring exceptional people, and creating an environment where talented individuals can do the best work of their careers.
The Role
Our customer base is expanding fast, and AI is central to how we scale and deliver value. We're looking for a senior-level Machine Learning Engineer who can move quickly while maintaining high quality, owning end-to-end ML pipelines while shaping product features that deliver real-world impact.
What You'll Do
  • Design, build, and maintain scalable machine learning models that improve and automate logistics processes for our customers.
  • Own projects end-to-end, from problem definition and data exploration to model deployment and monitoring in production.
  • Collaborate closely with engineering teams to align ML work with customer needs and deliver features that drive business value.
  • Serve as a technical leader and mentor within the ML area, reviewing code and ensuring best practices for reproducibility, quality, and performance.
  • Evaluate and implement tools and frameworks to improve our ML infrastructure and workflows.
  • Help shape the future of Canals as we continue scaling with our customers.
What You'll Bring
  • Senior-level experience building and deploying machine learning models in production environments.
  • Experience designing scalable data pipelines and working with large datasets.
  • Comfort taking ownership of projects and ensuring models deliver real, measurable customer value.
  • Strong Python skills with knowledge of ML frameworks (e.g., scikit-learn, PyTorch, TensorFlow) and data tools (e.g., Pandas, Spark).
  • Ability to guide and unblock others, providing thoughtful code reviews and architectural feedback.
  • Experience working independently in a fast-paced, product-focused environment.
  • Previous experience in high-growth startups or small teams is a plus.
  • Familiarity with MLOps practices and tools is a plus.
Why Join Canals
We're building software that solves real problems for an industry that keeps the world running. Our customers rely on our platform every day to operate their businesses.
We've found strong product-market fit and continue to grow quickly, creating opportunities for people who want to have a meaningful impact on the trajectory of a company.
We believe great people build great companies. That's why we invest heavily in hiring, development, and creating an environment where talented individuals can do the best work of their careers.
You'll work alongside ambitious, thoughtful teammates who care deeply about what they do, challenge each other directly, and have a lot of fun along the way.
We value ownership, transparency, and continuous improvement. Good ideas can come from anywhere, and people are trusted to make things happen.
We're remote-first, flexible, and distributed across North and South America, bringing together talented people from a wide range of backgrounds and experiences.
Canals.ai is an equal opportunity employer. In addition to EEO being the law, it is a policy that is fully consistent with our principles. All qualified applicants will receive consideration for employment without regard to status as a protected veteran or a qualified individual with a disability, or other protected status such as race, religion, color, national origin, sex, sexual orientation, gender identity, genetic information, pregnancy or age.

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