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Machine Learning Engineer Opt Jobs in Dayton, NJ

Attentive

Senior Machine Learning Engineer

New York, NY · On-site

$244K - $320K/yr

About the Role Our Machine Learning Engineering team powers personalized experiences for hundreds of millions of customers across thousands of brands. As a Senior Machine Learning Engineer, you will ...

Arlo

Machine Learning Engineer

New York, NY · On-site

$180K - $230K/yr

Arlo's underwriting is the core of the business, and it runs on machine learning at serious scale. We're hiring ML Engineer to build and own the infrastructure that powers it - from training models ...

Pangram

Machine Learning Engineer (Junior)

New York, NY · On-site

$135K - $150K/yr

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 ...

WireScreen

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 ...

S&P Global

Machine Learning Engineer II

New York, NY · On-site

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 ...

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All JobsMachine Learning Engineer Opt JobsMachine Learning Engineer Opt Jobs in Dayton, NJ

Machine Learning Engineer Opt information

See Dayton, NJ salary details

$32.3K

$131.9K

$198.2K

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

As of Sep 9, 2026, the average yearly pay for machine learning engineer opt in Dayton, NJ is $131,892.00, according to ZipRecruiter salary data. Most workers in this role earn between $104,000.00 and $158,800.00 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 Dayton, NJ?

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

What job categories do people searching Machine Learning Engineer Opt jobs in Dayton, NJ look for?

The top searched job categories for Machine Learning Engineer Opt jobs in Dayton, NJ are:

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

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

Machine Learning Engineer Opt jobs near you

Machine Learning Engineer (Technical Leadership)

New York, NY • On-site

Meta
Internet and IT • 10K+ employees
Learn more about Metaexternal

$271K/yr

Full-time

Posted 22 days ago

Meta rating

7.8

Company rating: 7.8 out of 10

Based on 45 frontline employees who took The Breakroom Quiz

139th of 247 rated software companies

Job description

Meta is seeking a Machine Learning Engineer to join our integrity engineering team. The ideal candidate will have deep industry experience building and deploying machine learning systems at scale, including model development, training infrastructure, and optimization. You will work on leveraging ML models to detect and enforce content to keep the platforms safe and create a better user experience across Meta's products — from payment fraud detection and click-through rate prediction to search ranking, content enforcement, and spam detection. This role involves applying advanced ML techniques to some of the most exciting and massive-scale prediction problems on the web.
Machine Learning Engineer (Technical Leadership) Responsibilities:
  • Drive the team's ML strategy & technical direction to pursue opportunities that advance machine learning capabilities across the organization
  • Design and develop end-to-end machine learning systems, from data pipelines to model training, evaluation, and deployment
  • Lead experimentation and A/B testing frameworks to measure and optimize model performance
  • Build highly scalable classifiers and ML tools leveraging deep learning, data regression, and rules-based models
  • Adapt and optimize machine learning methods for modern parallel environments (e.g., distributed clusters, multicore SMP, and GPU)
  • Partner with research teams to translate cutting-edge ML research into production systems
  • Mentor and influence ML engineers across organizations, raising the bar for ML best practices
  • Identify new ML opportunities for the larger organization and influence staffing/prioritization of these initiatives
  • Effectively communicate complex ML systems and architectural decisions to technical and non-technical stakeholders

Minimum Qualifications:
  • Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
  • Experience leading projects with industry-wide impact
  • Experience communicating and working across functions to drive solutions
  • Experience in mentoring/influencing engineers across organizations
  • Proven track record of planning multi-year roadmap in which short-term projects ladder to the long-term vision
  • Experience in driving large cross-functional/industry-wide engineering efforts
  • 12+ years of experience in programming languages (Python, C++, or Java) with technical background
  • 8+ years of experience in one or more of the following areas: machine learning, recommendation systems, pattern recognition, data mining or deep learning based methods

Preferred Qualifications:
  • Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
  • Experience with deep learning frameworks (PyTorch, TensorFlow) and ML infrastructure tools
  • Familiarity with MLOps practices, model monitoring, and production ML systems
  • Experience building and optimizing large-scale model training pipelines
  • Experience shipping ML-powered products to millions of users or launching new ML product lines
  • Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
  • Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
  • Publications or contributions to the ML research community

About Meta:
Meta builds technologies that help people connect, find communities, and grow businesses. When Facebook launched in 2004, it changed the way people connect. Apps like Messenger, Instagram and WhatsApp further empowered billions around the world. Now, Meta is moving beyond 2D screens toward immersive experiences like augmented and virtual reality to help build the next evolution in social technology. People who choose to build their careers by building with us at Meta help shape a future that will take us beyond what digital connection makes possible today—beyond the constraints of screens, the limits of distance, and even the rules of physics.
Meta is proud to be an Equal Employment Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law. Meta participates in the E-Verify program in certain locations, as required by law. Please note that Meta may leverage artificial intelligence and machine learning technologies in connection with applications for employment.
Meta is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance or accommodations due to a disability, please let us know at accommodations-ext@meta.com.
$271,000/year to $347,000/year + bonus + equity + benefits
Individual compensation is determined by skills, qualifications, experience, and location. Compensation details listed in this posting reflect the base hourly rate, monthly rate, or annual salary only, and do not include bonus, equity or sales incentives, if applicable. In addition to base compensation, Meta offers benefits. Learn more about benefits at Meta.

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