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Deep Learning Quantization Jobs in Irvington, NJ

Computer Vision/ML Engineer

New York, NY · On-site

$122K - $143K/yr

The position We are looking for our lead deep learning engineer to spearhead the development of our ... Optimize models for embedded deployment using quantization, pruning, TensorRT, and NVIDIA Triton

Computer Vision/ML Engineer

Brooklyn, NY

$117K - $138K/yr

The position We are looking for our lead deep learning engineer to spearhead the development of our ... Optimize models for embedded deployment using quantization, pruning, TensorRT, and NVIDIA Triton

Computer Vision/ML Engineer

New York, NY · On-site

$122K - $143K/yr

The position We are looking for our lead deep learning engineer to spearhead the development of our ... Optimize models for embedded deployment using quantization, pruning, TensorRT, and NVIDIA Triton

Implement techniques such as distillation, quantization, and pruning to aggressively accelerate ... Strong experience in deep learning systems and infrastructure * Expertise in PyTorch, CUDA, Triton ...

Implement techniques such as distillation, quantization, and pruning to aggressively accelerate ... Strong experience in deep learning systems and infrastructure * Expertise in PyTorch, CUDA, Triton ...

... quantization, compression, and resource-efficient AI, to drive performance improvements and ... Research experience in machine learning, deep learning, natural language processing, and/or ...

Deep dive into underlying codebases of TensorRT, PyTorch, TensorRT-LLM, vllm, sglang, CUDA, and ... Familiarity with LLM optimization techniques (e.g., quantization, speculative decoding, continuous ...

Showing results 21-40

Deep Learning Quantization information

See Irvington, NJ salary details

$11.2K

$85.6K

$142.8K

How much do deep learning quantization jobs pay per year?

As of Aug 7, 2026, the average yearly pay for deep learning quantization in Irvington, NJ is $85,565.00, according to ZipRecruiter salary data. Most workers in this role earn between $73,400.00 and $141,800.00 per year, depending on experience, location, and employer.

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

To excel as a Deep Learning Quantization Engineer, you need a strong background in machine learning, applied mathematics, and computer science, usually supported by an advanced degree in a related field. Familiarity with deep learning frameworks (such as TensorFlow or PyTorch), quantization toolkits, and hardware acceleration platforms is crucial. Analytical thinking, problem-solving, and clear technical communication are standout soft skills in this role. These abilities are essential for efficiently optimizing models for deployment on resource-constrained hardware while maintaining accuracy and performance.

What is the difference between Deep Learning Quantization vs Machine Learning Engineer?

AspectDeep Learning QuantizationMachine Learning Engineer
Required CredentialsAdvanced degrees in AI, Computer Science, or related fields; knowledge of neural networksBachelor's or Master's in CS, Data Science, or related fields; programming skills
Work EnvironmentResearch labs, AI development teams, hardware optimization settingsSoftware development teams, data-driven projects, product-focused environments
Industry UsageAI hardware optimization, model deployment, edge computingModel development, data analysis, software solutions across industries

Deep Learning Quantization focuses on reducing model size and improving inference speed through techniques like weight and activation quantization, often in hardware or embedded systems. Machine Learning Engineers develop, implement, and optimize machine learning models for various applications. While both roles require knowledge of AI and programming, Deep Learning Quantization is more specialized in model optimization techniques, whereas Machine Learning Engineers work broadly on model development and deployment.

What is deep learning quantization?

Deep learning quantization is the process of reducing the precision of the numbers used to represent a neural network's parameters, activations, or both. By converting the typically used 32-bit floating-point values to lower bit-width formats such as 16-bit or 8-bit integers, quantization significantly reduces the memory footprint and computational requirements of deep learning models. This technique helps deploy models efficiently on edge devices and mobile hardware while maintaining acceptable accuracy levels. Quantization is widely used in model optimization for faster inference and lower power consumption.

What are some common challenges faced when implementing deep learning quantization in production environments?

One of the main challenges in implementing deep learning quantization is balancing model accuracy with computational efficiency, as quantization can sometimes lead to a drop in model performance. Additionally, ensuring hardware compatibility and optimizing for different devices (such as CPUs, GPUs, or edge devices) can require extensive testing and tuning. Collaboration with data scientists, software engineers, and hardware specialists is often essential to successfully deploy quantized models at scale. Staying updated with the latest quantization techniques and frameworks is also important for overcoming these challenges.
What job categories do people searching Deep Learning Quantization jobs in Irvington, NJ look for? The top searched job categories for Deep Learning Quantization jobs in Irvington, NJ are:
What cities near Irvington, NJ are hiring for Deep Learning Quantization jobs? Cities near Irvington, NJ with the most Deep Learning Quantization job openings:

GenAI & AI/ML Framework Specialist

United Airlines

Manhattan, NY • On-site

Other

Medical, Dental, Vision, Life, Retirement, PTO

Posted 3 days ago

New


United Airlines rating

7.9

Company rating: 7.9 out of 10

Based on 341 frontline employees who took The Breakroom Quiz

7th of 26 rated airlines


Job description

Choosing Capgemini means choosing a company where you will be empowered to shape your career in the way you'd like, where you'll be supported and inspired bya collaborative community of colleagues around the world, and where you'll be able to reimagine what's possible. Join us and help the world's leading organizationsunlock the value of technology and build a more sustainable, more inclusive world.

Job Location : New York, NY / Arlington, VA (Onsite/Hybrid from Day 1)
Job Description

We are seeking a highly skilled GenAI & AI/ML Framework Specialist to design, develop, and scale next-generation Artificial Intelligence solutions. This role will focus on building advanced machine learning and Generative AI applications, optimizing open-source AI frameworks, and integrating AI-powered capabilities into enterprise platforms.

The ideal candidate will possess deep expertise in AI/ML frameworks, Large Language Models (LLMs), MLOps, cloud platforms, and modern data infrastructure. You will work closely with product, engineering, and data science teams to deliver high-performance, production-ready AI solutions that drive business value.

Key Responsibilities
  • Design and implement Generative AI solutions using LLMs, RAG, prompt engineering, and fine-tuning techniques.
  • Develop, train, and optimize machine learning and deep learning models.
  • Build scalable AI/ML pipelines for data processing, model training, and deployment.
  • Integrate AI models into enterprise applications and production environments.
  • Improve model inference performance, scalability, and cost efficiency.
  • Collaborate with cross-functional teams to deliver AI-driven business solutions.
Required Skills
  • Expertise in PyTorch, TensorFlow, or JAX.
  • Hands-on experience with Hugging Face, LangChain, LlamaIndex, and vLLM.
  • Strong Python programming skills.
  • Solid understanding of machine learning, deep learning, Transformers, CNNs, and RLHF.
  • Experience with vector databases (Pinecone, ChromaDB, Milvus) and SQL/NoSQL databases.
  • Knowledge of MLOps tools such as MLflow, Kubeflow, or Triton Inference Server.
  • Experience with cloud platforms such as AWS SageMaker, Azure AI, or GCP Vertex AI, and GPU acceleration (CUDA).
Required Qualifications
  • Bachelor's or Master's degree in Computer Science, Data Science, Mathematics, Engineering, or a related quantitative discipline.
  • Minimum 8 years of experience in Data Science, Machine Learning Engineering, or AI Engineering.
  • At least 2 years of hands-on experience in Generative AI, including LLM-based solutions and enterprise AI deployments.
  • Proven experience designing, developing, and deploying production-grade AI/ML applications.
  • Strong analytical, problem-solving, and communication skills.
  • Ability to collaborate effectively in a fast-paced, cross-functional environment.
Preferred Qualifications
  • Experience with enterprise-scale AI transformation initiatives.
  • Knowledge of model governance, responsible AI, and AI security frameworks.
  • Experience working with multi-modal AI applications involving text, image, audio, or video models.
  • Exposure to distributed training, model compression, quantization, and inference optimization techniques.
  • Familiarity with agentic AI architectures and autonomous workflow orchestration.

The base compensation range for this role in the posted location is: 85786- 105237

Capgemini provides compensation range information in accordance with applicable national, state, provincial, and local pay transparency laws. The base compensation range listed for this position reflects the minimum and maximum target compensation Capgemini, in good faith, believes it may pay for the role at the time of this posting. This range may be subject to change as permitted by law.

The actual compensation offered to any candidate may fall outside of the posted range and will be determined based on multiple factors legally permitted in the applicable jurisdiction.

These may include, but are not limited to: Geographic location, Education and qualifications, Certifications and licenses, Relevant experience and skills, Seniority and performance, Market and business consideration, Internal pay equity.

It is not typical for candidates to be hired at or near the top of the posted compensation range.

In addition to base salary, this role may be eligible for additional compensation such as variable incentives, bonuses, or commissions, depending on the position and applicable laws.

Capgemini offers a comprehensive, non-negotiable benefits package to all regular, full-time employees. In the U.S. and Canada, available benefits are determined by local policy and eligibility and may include: 

  • Paid time off based on employee grade (A-F), defined by policy: Vacation: 12-25 days, depending on grade, Company paid holidays, Personal Days, Sick Leave
  • Medical, dental, and vision coverage (or provincial healthcare coordination in Canada)
  • Retirement savings plans (e.g., 401(k) in the U.S., RRSP in Canada)
  • Life and disability insurance
  • Employee assistance programs
  • Other benefits as provided by local policy and eligibility

Important Notice: Compensation (including bonuses, commissions, or other forms of incentive pay) is not considered earned, vested, or payable until it becomes due under the terms of applicable plans or agreements and is subject to Capgemini's discretion, consistent with applicable laws. The Company reserves the right to amend or withdraw compensation programs at any time, within the limits of applicable legislation.

Disclaimers

Capgemini is an Equal Opportunity Employer encouraging inclusion in the workplace. Capgemini also participates in the Partnership Accreditation in Indigenous Relations (PAIR) program which supports meaningful engagement with Indigenous communities across Canada by promoting fairness, accessibility, inclusion and respect.  We value the rich cultural heritage and contributions of Indigenous Peoples and actively work to create a welcoming and respectful environment. All qualified applicants will receive consideration for employment without regard to race, national origin, gender identity/expression, age, religion, disability, sexual orientation, genetics, veteran status, marital status or any other characteristic protected by law.

This is a general description of the Duties, Responsibilities and Qualifications required for this position. Physical, mental, sensory or environmental demands may be referenced in an attempt to communicate the manner in which this position traditionally is performed. Whenever necessary to provide individuals with disabilities an equal employment opportunity, Capgemini will consider reasonable accommodations that might involve varying job requirements and/or changing the way this job is performed, provided that such accommodation does not pose an undue hardship. Capgemini is committed to providing reasonable accommodation during our recruitment process. If you need assistance or accommodation, please reach out to your recruiting contact.

Please be aware that Capgemini may capture your image (video or screenshot) during the interview process and that image may be used for verification, including during the hiring and onboarding process.

Click the following link for more information on your rights as an Applicant in the United States.  http://www.capgemini.com/resources/equal-employment-opportunity-is-the-law

Capgemini is a global business and technology transformation partner, helping organizations to accelerate their dual transition to a digital and sustainable world, while creating tangible impact for enterprises and society. It is a responsible and diverse group of 340,000 team members in more than 50 countries. With its strong over 55-year heritage, Capgemini is trusted by its clients to unlock the value of technology to address the entire breadth of their business needs. It delivers end-to-end services and solutions leveraging strengths from strategy and design to engineering, all fueled by its market leading capabilities in AI, generative AI, cloud and data, combined with its deep industry expertise and partner ecosystem.


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About United Airlines

Sourced by ZipRecruiter

United Airlines is embarking on an exciting journey to become the best airline in aviation history. Our purpose, "Connecting People, Uniting the World," extends beyond transportation, emphasizing our commitment to uplift and create opportunities in the places we serve. With a global presence and diverse workforce, we value inclusivity and are dedicated to hiring tens of thousands of individuals across various roles. Our comprehensive benefits package, including perks like space available travel, parental leave, and 401k, aims to support your well-being and growth.

Industry

Aviation

Company size

10,000+ Employees

Headquarters location

Chicago, IL, US

Year founded

1926

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