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Senior Natural Language Processing Engineer Jobs in New York

SonSoft Inc.

Sr. Data Scientist

Newark, NJ · On-site

They are seeking a Senior Data Scientist with extensive experience in machine learning algorithms and strong skills in Text Mining and Natural Language Processing. Responsibilities : • 10 to 15 ...

J.P. Morgan

Applied AI/ML Lead - Payments

New York, NY

  • Medical

  • Retirement

Communicate tradeoffs and recommendations to senior stakeholders, translating model behavior into ... natural language processing solutions with measurable outcomes in production. * Strong programming ...

Centstone

Senior GenAI Engineer

Jersey City, NJ · On-site

$60 - $70/hr

Senior GenAI Engineer Location: Jersey City, NJ (Onsite) Pay Rate: $60-$70/Hour Contract: Contract ... Strong expertise in Generative AI, Large Language Models (LLMs), Natural Language Processing (NLP ...

Soni Resources

Senior AI/ML Engineer

New York, NY · On-site

$200K/yr

We are seeking a Senior AI/ML Engineer to help design, build, and scale advanced analytics and ... Experience with natural language processing and natural language understanding * Experience leading ...

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Senior Natural Language Processing Engineer information

What is the difference between Senior Natural Language Processing Engineer vs Data Scientist?

AspectSenior Natural Language Processing EngineerData Scientist
Required CredentialsAdvanced degree in CS, NLP, or related field; experience with NLP frameworksDegree in CS, statistics, or related; data analysis skills
Work EnvironmentDevelops NLP models, algorithms, and language-specific toolsAnalyzes data, builds predictive models, visualizes insights
Employer & Industry UsageTech companies, AI startups, research institutions focusing on language techVarious industries including finance, healthcare, marketing

While both roles require strong analytical skills and programming knowledge, Senior NLP Engineers specialize in language-specific models and algorithms, whereas Data Scientists focus on broader data analysis and predictive modeling across various data types.

What are some common challenges faced by senior natural language processing engineers when deploying NLP models to production?

Senior NLP Engineers often encounter challenges such as ensuring model scalability, maintaining accuracy with real-world data, and addressing data privacy concerns. Deploying models at scale requires optimizing for speed and efficiency, as well as monitoring performance to handle domain shifts or unexpected inputs. Collaboration with DevOps and data engineering teams is crucial to integrate models seamlessly into existing pipelines and to ensure robust, maintainable solutions.

What does a senior natural language processing engineer do?

A Senior Natural Language Processing (NLP) Engineer designs and implements advanced algorithms that enable computers to understand, interpret, and generate human language. They work on tasks such as text classification, sentiment analysis, machine translation, and conversational AI. In addition to developing NLP models, they often lead projects, mentor junior team members, and collaborate with data scientists, software engineers, and product managers to build and deploy language-based applications. Their expertise helps organizations leverage language data to solve complex problems and improve user experiences.

What are the key skills and qualifications needed to thrive as a senior natural language processing engineer, and why are they important?

To thrive as a Senior Natural Language Processing Engineer, you need a deep understanding of machine learning, linguistics, and advanced programming skills in languages like Python, typically backed by a degree in computer science or a related field. Familiarity with NLP frameworks (such as spaCy, NLTK, or Hugging Face), cloud platforms, and experience with deep learning libraries like TensorFlow or PyTorch are crucial. Strong problem-solving abilities, effective communication, and the ability to work collaboratively in multidisciplinary teams are standout soft skills. These skills and qualities are essential for developing, deploying, and refining language-based AI solutions that meet complex business and user needs.

What are the most commonly searched types of Natural Language Processing Engineer jobs in New York?

The most popular types of Natural Language Processing Engineer jobs in New York are:

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Senior Natural Language Processing Engineer jobs near you

AI Developer Natural Language Processing Machine Learning AWS

Accord Technologies Inc.

New York, NY • On-site

Contractor

Re-posted 9 days ago

Job description

AI Developer – Natural Language Processing,  Machine Learning & AWS 
Loction: New York, NY  (Need Onsite day 1, hybrid 3 days from office).
Duraiton: Long term
Position type: W2 contract

Job Description:

We are seeking a highly skilled and motivated AI Developer specializing in Natural Language Processing (NLP) and Large Language Models (LLMs) to join our dynamic team. The ideal candidate will have strong hands-on experience in implementing LLMs, managing machine learning pipelines, and deploying AI solutions on cloud and server environments. Experience in the financial sector, particularly in equities, will be considered an advantage. 

Responsibilities:

  • Develop, implement, and optimize NLP solutions utilizing LLMs tailored for financial data and equities
  • Manage and deploy Machine Computing Platforms (MCP) to support scalable AI workloads.
  • Collaborate with data scientists and engineers to integrate AI models into production environments.
  • Maintain and enhance AI infrastructure on AWS cloud services and Linux-based servers.
  • Apply traditional machine learning techniques on structured large datasets to complement NLP efforts.
  • Troubleshoot and resolve software/hardware issues related to AI systems and server environments.
  • Stay updated with the latest advancements in NLP, LLMs, and machine learning best practices.

Requirements:

  • Deep knowledge of Natural Language Processing, including expertise with Large Language Models (e.g., GPT, BERT, similar architectures).
  • Hands-on experience in implementing, fine-tuning, and deploying LLMs in production.
  • Proven experience managing and operating MCP or similar machine learning platforms.
  • Strong proficiency with AWS cloud services (EC2, S3, Lambda, etc.) and experience working with Linux server environments.
  • Knowledge of traditional machine learning models applied on structured big data is a plus.
  • Prior experience in equities or financial data analysis is highly preferred.
  • Programming proficiency in Python, and familiarity with relevant AI frameworks (e.g., TensorFlow, PyTorch, Hugging Face).
  • Strong problem-solving skills and ability to work in a fast-paced, collaborative environment. 
Preferred,
  • Hands-on experience deploying AI models in financial or equities contexts.
  • Familiarity with data pipeline development and big data processing tools.