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Machine Learning Engineer Opt Jobs in Hoboken, NJ

Machine Learning Engineer

Manhattan, NY · On-site

$150 - $200/hr

Our team is a passionate mix of engineers across electrical, firmware, software, and machine learning. Core Responsibilities * Architect Physics Foundation Models: Design and train deep learning ...

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 ...

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 ...

Machine Learning Engineer

Manhattan, NY · On-site

$125 - $150/hr

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 ...

Machine Learning Engineer

New York, NY · On-site +1

$209K - $250K/yr

Machine Learning Engineer Location: 55 Water Street, New York, NY 10041 (Telecommuting permitted within normal commuting distance of New York, NY office) Job Duties: Kensho Technologies LLC seeks a ...

Our team is a passionate mix of engineers across electrical, firmware, software, and machine learning. Core Responsibilities * Architect Physics Foundation Models: Design and train deep learning ...

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 ...

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 ...

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 ...

Machine Learning Engineer

Manhattan, NY · On-site

$125 - $150/hr

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 ...

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 ...

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 ...

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 ...

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 ...

Showing results 41-60

Machine Learning Engineer Opt information

See Hoboken, NJ salary details

$34.5K

$140.9K

$211.7K

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

As of Sep 8, 2026, the average yearly pay for machine learning engineer opt in Hoboken, NJ is $140,884.00, according to ZipRecruiter salary data. Most workers in this role earn between $111,000.00 and $169,600.00 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 Hoboken, NJ?

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

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

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

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

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

Machine Learning Engineer

Manhattan, NY • On-site

$150 - $200/hr

Other

Re-posted 15 hours ago


Job description

About the company

Root Access is a frontier electronics company. We are a NYC-based startup funded by top investors. Our team is a passionate mix of engineers across electrical, firmware, software, and machine learning.

Core Responsibilities
  • Architect Physics Foundation Models: Design and train deep learning models.

  • Build the ECAD Data Pipeline: Develop high-performance asset pipelines to convert geometric, discrete, and multi-layer PCB files (ODB++, IPC-2581, STEP, Gerber) into continuous space data.

  • Multi-Modal Architecture Integration: Collaborate on connecting upstream Graph Neural Networks (GNNs) or LLMs mapping schematic topologies to downstream spatial physics engines.

  • Optimize for Real-Time Execution: Optimize training and inference pipelines on GPU clusters.

Required Technical Skills & Qualifications
  • Education: Master’s or Ph.D. in Computer Science, Mathematics, EE, Physics, or a related quantitative field with a focus on Scientific Machine Learning (SciML).

  • Deep Learning Frameworks: 4+ years of expert-level experience with PyTorch or JAX.

  • SciML Expertise: Direct, hands‑on experience building and training PINNs, FNOs, etc.

  • Mathematical Depth: Exceptional understanding of partial differential equations (PDEs), vector calculus, automatic differentiation (autograd), and numerical optimization algorithms (Adam, L‑BFGS).

  • Data Pipelines: Strong proficiency in manipulating spatial or geometric datasets using Python libraries (NumPy, SciPy, Shapely, Open3D, or custom voxelization matrices).

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