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Python Llm Jobs in Red Bank, NJ (NOW HIRING)

Pwc

GenAI Python Systems Engineer-Manager

New York, NY

$99K - $232K/yr

... Python and SQL - Experience with Docker and containerized deployments - Skilled in AI techniques ... LLM optimization - Implementing data integration solutions using AWS, Azure, GCP - Utilizing AWS ...

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Python Llm information

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How much do python llm jobs pay per hour?

As of Jul 14, 2026, the average hourly pay for python llm in Red Bank, NJ is $60.16, according to ZipRecruiter salary data. Most workers in this role earn between $49.57 and $68.32 per hour, depending on experience, location, and employer.

What is a Python LLM job?

A Python LLM job involves working with Large Language Models (LLMs) using Python to develop, fine-tune, and deploy AI models. Responsibilities may include data preprocessing, prompt engineering, model optimization, and integration with applications. Professionals in this role often work with frameworks like TensorFlow, PyTorch, or Hugging Face Transformers. They may also contribute to improving model efficiency, reducing bias, and ensuring ethical AI usage.

What are the key skills and qualifications needed to thrive in the Python Llm position, and why are they important?

To excel as a Python LLM (Large Language Model) Engineer, you need strong skills in Python programming, machine learning, and natural language processing, typically supported by a degree in computer science or a related field. Proficiency with libraries such as TensorFlow, PyTorch, Hugging Face Transformers, and experience with model deployment platforms are often essential, alongside certifications in AI or data science. Effective communication, problem-solving abilities, and collaboration are important soft skills for working in interdisciplinary teams and delivering results in dynamic environments. These skills ensure the development, fine-tuning, and deployment of advanced language models that meet both technical and business objectives.

What are some common challenges faced by Python LLM Engineers in their daily work?

Python LLM Engineers often encounter challenges related to optimizing model performance, managing large datasets, and adapting models to specific business needs. Working with large-scale language models requires balancing computational resource limitations with the need for high accuracy and efficiency. Collaboration with data scientists, product managers, and DevOps engineers is routine to ensure seamless model integration and deployment. Staying updated on the latest advancements in NLP and continuously improving models based on user feedback are also important aspects of the role.

What job categories do people searching Python Llm jobs in Red Bank, NJ look for? The top searched job categories for Python Llm jobs in Red Bank, NJ are:
What cities near Red Bank, NJ are hiring for Python Llm jobs? Cities near Red Bank, NJ with the most Python Llm job openings:
Python Llm jobs near you

Gen AI / ML Full Stack Engineer, orchestration, Python/Java, RAG, LLMOps, Vectors, 12+ Mths Cont NYC

ZnA Inc

New York, NY • On-site

Contractor

Re-posted 3 days ago

Job description

 Gen AI / ML Full Stack Engineer, orchestration, Python/Java, RAG, LLMOps, Vectors, 12+ Mths Cont NYC

JPC – 3566

Level 3 : 5 to 8  Years of Industry exp

LOCATION:   New York ( 3 days hybrid, inperson interview will be needed ) 

Duration : 12+ months

Title: Gen AI / ML Full Stack Engineer , orchestration framework (Langchains etc), Python/Java, RAG, LLMOps, Adv Vectors (ColBERT/chunking), production failures, Fixed Income / Lending Platforms 12+ Mths Cont NYC

Description:

 Applied AI Engineer Overview

Morgan Stanleys Fixed Income Institutional Lending Technology team is building an enterprise grade GenAI workflow platform to enable document data extraction, embedded productivity assistants, and automated business workflows across business lines.

This is not a research or demo role.

We are seeking senior hands-on full stack engineers who have designed, built, and operated GenAI systems in production, and understand failure modes, evaluation, and governance as first class AI-powered systems.

What Youll Do Design and evolve reusable GenAI workflows used across Lending business lines.

  • Develop an enterprise grade AI-based document ingestion and data extraction capability, including traceability, confidence scoring, and human-in-the-loop review.
  • Build AI-powered assistants embedded in Lending systems using agentic workflows.
  • Deliver automated content and deck generation workflows for reporting and approvals.
  • Provide expert advice on GenAI architecture including model selection, orchestration patterns, and evaluation strategy.
  • Establish LLMOps practices: extraction accuracy, assistant reliability, prompts management, and audit monitoring.
  • Design and implement controls for entitlements, PII handling within open-source models in a regulated environment.
  • In the role you are expected to act as a hands-on technical expert, and it has a clear path to becoming a platform owner responsible for shared GenAI standards across Lending.

What Youll Bring

  • 2+, dedicated experience in practical application of GenAI solutions in an enterprise business environment.
  • Designing and operating GenAI orchestration frameworks in production beyond vendor examples (e.g., LangChain systems),
  • 5+ years of strong front-to-back engineering experience, focusing on AI ML platforms and workflows (Python or Java).
  • Proven experience building and operating production grade GenAI / LLM platforms, applying patterns such as RAG, tool/function calling, agentic workflows, and validated structured outputs.
  • Strong LLMOps expertise, including evaluation harnesses, prompt and version management, regression testing, observability, and reliability measurement in production systems.
  • Hands on experience building AI-first data ingestion pipelines with measurable quality, accuracy, and reliability.
  • Advanced retrieval experience advanced vector search, including multi vector and late interaction approaches (e.g., ColBERT, chunking), multi stage retrieval pipelines, metadata filtering, reranking.
  • Solid understanding of evaluation metrics and how they shape practical RAG system design (e.g., recall vs precision, latency vs quality, MRR, NDCG).
  • Experience operating GenAI systems through real production failures (model regressions, retrieval degradation, prompt drift, data quality issues) and designing mitigation strategies.
  • Nice to Have Fixed Income or Institutional Lending domain experience. Experience working in regulated environments with strong audit and control requirements.
  • Familiarity with enterprise security, data governance, and entitlement models.
  • Experience designing reusable internal platforms or shared developer tooling. Frontend experience is beneficial (Angular or React)