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Machine Learning Engineer Opt Jobs in Edison, NJ

Jane Street

Machine Learning Engineer

Manhattan, NY · On-site

We are looking for an engineer with robust experience in machine learning and strong mathematical foundations to join our growing ML team and to help drive the direction of our ML platform. Machine ...

Indeed

Machine Learning Engineer

Manhattan, NY · On-site

As a Machine Learning Engineer, you will prepare datasets, train and optimize models, and maintain and improve model inference services. You will learn and apply new techniques from open source ...

Jane Street

Machine Learning Engineer

New York, NY

We are looking for an engineer with robust experience in machine learning and strong mathematical foundations to join our growing ML team and to help drive the direction of our ML platform. Machine ...

Jane Street

Machine Learning Engineer

New York, NY · On-site

We are looking for an engineer with robust experience in machine learning and strong mathematical foundations to join our growing ML team and to help drive the direction of our ML platform. Machine ...

Button

Senior Machine Learning Engineer

Manhattan, NY · On-site

$153K - $198K/yr

Senior Machine Learning Engineer Button's mission is to empower the companies shaping the creator and affiliate economy - fueling mobile growth with innovation and new paths to monetization. Today ...

Colgate-Palmolive

Machine Learning Engineer

Manhattan, NY · On-site

$130K - $170K/yr

Machine Learning Engineer Established in 1806 as a small soap and candle business in New York City, Colgate-Palmolive is now a truly global company with products sold in over 200 countries and ...

Kitware

Machine Learning Engineer

New York, NY · On-site

$85K - $125K/yr

... machine learning, artificial intelligence, and computer vision * Perform rapid prototyping and enhanced development to be integrated into operational systems * Contribute your strong programming ...

InstantServe LLC

Machine Learning Engineer

Manhattan, NY · Hybrid

$126K - $151K/yr

Machine Learning Engineer Location: Long Island City, NY 11101 (Onsite 4 Days/week) Type: Permanent Full Time About the Role: In this role, you will take the lead in developing and fine-tuning ...

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.

Teleskope

Machine Learning Engineer

Manhattan, NY · Hybrid

$115K - $158K/yr

Senior Machine Learning Engineer Teleskope is redefining data security for the AI era with the only dedicated platform that combines precise visibility with automated remediation. Teleskope ...

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 ...

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 ...

Indeed

Machine Learning Engineer III

Manhattan, NY · On-site

Comscore, Total Visits, March 2025) Day to Day As a Machine Learning Engineer III, you will be a team lead. You will own one of the team's major workstreams, help drive technical direction for the ...

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

Machine Learning Engineer Opt information

See Edison, NJ salary details

$32.6K

$133.3K

$200.3K

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

As of Jun 24, 2026, the average yearly pay for machine learning engineer opt in Edison, NJ is $133,308.00, according to ZipRecruiter salary data. Most workers in this role earn between $105,100.00 and $160,500.00 per year, depending on experience, location, and employer.

What are Machine Learning Engineers?

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 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.

Is a machine learning engineer still in demand?

Yes, machine learning engineers are in high demand due to the growing adoption of AI and data-driven solutions across industries. They are sought after for their skills in programming, data analysis, and familiarity with tools like Python, TensorFlow, and cloud platforms, making this a strong career choice for those with relevant expertise.

Which 5 jobs will survive AI?

Machine Learning Engineers are likely to continue to be in demand as AI advances because they develop and refine AI models, requiring specialized skills in programming, data analysis, and domain knowledge. Jobs that involve complex problem-solving, creativity, and emotional intelligence, such as healthcare professionals, educators, and skilled tradespeople, are also expected to persist despite AI automation. Continuous learning and adapting to new tools and technologies will be essential for job security across many fields.

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 a $900,000 AI job?

A $900,000 AI-related job typically refers to high-level roles such as senior machine learning engineers, AI research directors, or chief AI officers, often in large tech companies or specialized firms. These positions usually require advanced skills in machine learning, deep learning, and data science, along with extensive experience and leadership responsibilities.

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 engineers make $500,000?

Senior machine learning engineers with extensive experience, advanced skills in deep learning and data science, and often working in high-paying industries such as finance or tech, can earn $500,000 or more annually. Compensation typically includes base salary, bonuses, and stock options, especially at large tech companies or startups with significant funding.
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Machine Learning Engineer Opt jobs near you
Machine Learning Engineer

Machine Learning Engineer

The Associated Press

Manhattan, NY • On-site

Full-time

Posted 26 days ago

Job description

Job Summary:
The Associated Press is an independent global news organization dedicated to factual reporting. They are seeking a Machine Learning Engineer to shape how they build and scale machine learning systems, focusing on developing and optimizing ML inference systems that process large volumes of media data.
Responsibilities:
• Design, build, and scale ML-powered inference systems that process large volumes of text, image, and video data to power news-based intelligence products.
• Productionize and optimize state of the art models and inference pipelines. These models include, but are not limited to:
• + DistilBERT for Named Entity Recognition (NER) over hundreds of thousands of search queries/day
• + TransNetV2 for video shot boundary detection at scale for archival video as well as real-time
• + SBERT for embedding generation from textual descriptions
• + External multimodal APIs for image/video captioning
• Support hybrid search architectures by defining embedding/re-ranking interfaces, evaluation metrics, and inference performance requirements; partner with search/platform engineers on index configuration, sharding, and cluster tuning.
• Design and implement scalable data processing pipelines across hybrid CPU/GPU environments to handle millions of media assets.
• Partner with MLOps and platform engineering to enable the deployment and operation of ML systems reliably, contributing to:
• + Distributed inference architectures
• + Cloud-based execution (e.g., AWS EC2, Batch, Lambda, SageMaker)
• + Efficient resource utilization across workloads
• Optimize inference latency and throughput across distributed workloads using cloud-based resources (AWS EC2, Batch, Lambda, SageMaker, etc.)
• Build resilient asynchronous processing systems for large-scale workloads, ensuring:
• + Reliability (retries, fault tolerance)
• + Efficiency (caching, deduplication)
• + Observability (metrics, logging, traceability)
• Work closely with data scientists and product teams to iterate on models, improve performance, and deliver measurable impact in production.
Qualifications:
Required:
• 8+ years of experience building production ML inference systems.
• Demonstrated ownership of deep-learning inference optimization in production (quantization, distillation, compilation, kernel/profile-level performance work) for transformer NLP and/or CV models.
• Experience with both TensorFlow (SavedModel, tf.data, XLA, TFLite) and PyTorch (TorchScript, ONNX, FastAPI/TorchServe)
• Hands-on experience optimizing inference pipelines on AWS infrastructure, ideally across different types of media assets.
• Experience with video frameworks/tools (e.g., FFmpeg), and working with large-scale frame-level inference.
• Demonstrated experience monitoring and debugging model latency, memory, and pipeline throughput.
• Experience with hybrid search architectures (BM25 + vector search + cross-encoder reranking).
• Familiarity with OpenAI APIs or other foundation model providers.
• Familiarity with open source HuggingFace LLMs.
• Experience with data pipeline and workflow orchestration tools (e.g., Airflow)
Company:
The Associated Press is a source of independent newsgathering, supplying a steady stream of news to its members, and more. Founded in 1846, the company is headquartered in New York, USA, with a team of 1001-5000 employees. The company is currently Late Stage.

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