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Remote Retrieval Augmented Generation Jobs in Secaucus, NJ

AI/ ML Engineer

New York, NY ยท Remote

$60 - $62/hr

US/ Canada- Remote Minimum exp. required: 8+ yrs. We are looking for a GenAI Engineer to design ... Implement prompt engineering, RAG (Retrieval-Augmented Generation), and fine-tuning techniques

VP, Data & Analytics

New York, NY ยท Remote

$196K - $253K/yr

Build secure enterprise Retrieval-Augmented Generation (RAG) platforms leveraging proprietary healthcare knowledge and enterprise content * Design, deploy, and manage AI agents that automate clinical ...

Data & AI Engineer

New York, NY ยท On-site +1

$125K - $150K/yr

The Data & AI Engineer will implement retrieval-augmented generation (RAG) patterns, embedding and indexing pipelines, vector stores, and semantic models alongside core ELT, streaming, and analytical ...

Experience with RAG (Retrieval-Augmented Generation) architectures (e.g., GraphRAG, hybrid search). * Strong background in cloud architecture (AWS, GCP, or Azure) and containerization (Docker ...

New

Familiarity with Large Language Models (LLMs) and Retrieval Augmented Generation (RAG) * Ability to collaborate effectively across technical and non-technical teams What we offer * Drive growth in a ...

Familiarity with Large Language Models (LLMs) and Retrieval Augmented Generation (RAG) * Ability to collaborate effectively across technical and non-technical teams What we offer * Drive growth in a ...

Knowledge of vector databases (Pinecone, Weaviate, ChromaDB) and RAG (Retrieval-Augmented Generation) architectures. Familiarity with the developer tool ecosystem (GitHub API, Jira API, GitLab) for ...

You will work closely with engineering, data science, and infrastructure teams to build scalable AI-driven applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), model ...

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Remote Retrieval Augmented Generation information

What are the key skills and qualifications needed to thrive as a Remote Retrieval Augmented Generation Engineer, and why are they important?

To thrive as a Remote Retrieval Augmented Generation (RAG) Engineer, you need a strong background in machine learning, natural language processing, and information retrieval, often backed by a degree in computer science or a related field. Familiarity with tools and frameworks like PyTorch, TensorFlow, Hugging Face Transformers, and experience with retrieval systems such as Elasticsearch or FAISS are typically required. Problem-solving, effective communication, and adaptability are important soft skills for collaborating remotely and iterating on rapidly evolving AI solutions. These skills ensure the engineer can design, deploy, and optimize robust RAG systems that effectively combine retrieval and generation for high-quality AI outputs.

What is the difference between Remote Retrieval Augmented Generation vs Remote Data Scientist?

AspectRemote Retrieval Augmented GenerationRemote Data Scientist
CredentialsAI/ML knowledge, programming skillsStatistics, programming, domain expertise
Work EnvironmentAI development, NLP projectsData analysis, model building
Industry UsageAI, NLP, machine learningTech, finance, healthcare
Search & ComparisonOften compared for AI roles involving language modelsCompared for data analysis roles

Remote Retrieval Augmented Generation focuses on developing AI models that combine retrieval techniques with language generation, requiring expertise in AI, NLP, and programming. Remote Data Scientists analyze data, build models, and interpret results, often with statistical and domain knowledge. While both roles may work remotely and involve data handling, Retrieval Augmented Generation emphasizes AI model development, whereas Data Scientists focus on data analysis and insights.

What are some common challenges faced by professionals working in Remote Retrieval Augmented Generation roles, and how can they be addressed?

Professionals in Remote Retrieval Augmented Generation (RAG) roles often encounter challenges related to integrating diverse data sources, ensuring low latency in information retrieval, and maintaining the quality and relevance of augmented outputs. Coordinating effectively with distributed teams and adapting to rapidly evolving AI technologies are also common hurdles. To address these, staying current with best practices in data engineering, leveraging robust APIs, and participating in regular team check-ins can help ensure smooth collaboration and system performance.

What is Remote Retrieval Augmented Generation?

Remote Retrieval Augmented Generation (RAG) is an advanced AI technique that combines large language models with external information sources. In a remote RAG setup, the model retrieves relevant data from remote databases or APIs during the generation process, enhancing its responses with up-to-date or domain-specific knowledge. This approach is widely used in applications that require accurate, context-aware answers, such as chatbots, search engines, and virtual assistants. By leveraging remote retrieval, RAG systems can access a broader range of information without needing to store all data locally.
What are popular job titles related to Remote Retrieval Augmented Generation jobs in Secaucus, NJ? For Remote Retrieval Augmented Generation jobs in Secaucus, NJ, the most frequently searched job titles are:
What job categories do people searching Remote Retrieval Augmented Generation jobs in Secaucus, NJ look for? The top searched job categories for Remote Retrieval Augmented Generation jobs in Secaucus, NJ are:
What cities near Secaucus, NJ are hiring for Remote Retrieval Augmented Generation jobs? Cities near Secaucus, NJ with the most Remote Retrieval Augmented Generation job openings:
Sr Machine Learning / AI Engineer - Remote

Sr Machine Learning / AI Engineer - Remote

NAVA Software Solutions

Jersey City, NJ โ€ข On-site, Remote

$134K - $176K/yr

Full-time

Posted 26 days ago


Job description

NAVA Software solutions is looking for a Senior Machine Learning / AI Engineer
Details:
Senior Machine Learning / AI Engineer
Location: Remote
Duration: 1+ year
About the Project
The team has developed an intelligent search solution that includes mobile integration. The next phase focuses on extending member benefits and provider search capabilities to enable greater self-service, while leveraging AI to support intentional prompting and member decision-making.
The selected candidate will play a key role in enhancing AI-driven features, integrating advanced models, and strengthening the data and deployment pipeline across multiple platforms and channels.
Summary of Duties & Responsibilities
  • Design, develop, and implement AI/ML models and frameworks to enhance member experience and decision-making.
  • Extend intelligent search functionalities with advanced natural language and retrieval capabilities.
  • Build and manage ML pipelines connecting platform, AI, and channel teams (DevOps focus).
  • Implement Retrieval-Augmented Generation (RAG) and work with Large Language Models (LLMs) for conversational and decision-support systems.
  • Apply Model Context Protocols (MCPs) and integrate Knowledge Bases for contextual and dynamic AI responses.
  • Collaborate with cross-functional teams to embed AI-driven insights into digital member experiences.
  • Serve as a liaison between the enterprise AI team and application/DHP teams to ensure smooth integration.
  • Support onboarding, configuration, and integration of new AI components and models.
  • Participate in testing, validation, and continuous improvement of deployed AI models and systems.
  • Collaborate with data engineering teams to ensure AI models are integrated with data pipelines, data lakes, and enterprise systems.

Required Skills & Qualifications
  • Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related field.
  • 3+ years of experience in Machine Learning, Artificial Intelligence, or related software engineering roles.
  • Proven experience designing and coding AI/ML solutions end-to-end (Python, PyTorch, TensorFlow, etc.).
  • Strong understanding of Retrieval-Augmented Generation (RAG) and Large Language Models (LLMs).
  • Experience implementing or utilizing Model Context Protocols (MCPs).
  • Understanding of Knowledge Base architecture and integration into enterprise applications.
  • Hands-on experience with DevOps practices for ML pipelines and model deployment (CI/CD, containerization, monitoring).
  • Experience deploying AI solutions in cloud environments (Azure or AWS preferred).
  • Familiarity with data storage, ETL processes, and integration with enterprise data systems.
  • Excellent communication and collaboration skills, able to interface between technical and business teams.

Preferred Qualifications
  • Experience in healthcare or member services domains.
  • Familiarity with intelligent search systems, recommendation engines, or conversational AI.
  • Knowledge of data governance, model security, and compliance best practices.
  • Experience working in agile environments (Scrum, Kanban).
  • Exposure to MLOps practices and cloud data pipelines.

NAVA Software Solutions logo

About NAVA Software Solutions

Sourced by ZipRecruiter

NAVA is a strategic partner for companies seeking to develop or customize software and products. Our team of experts leverages cutting-edge technology and deep industry knowledge to provide customized solutions that drive business success. Whether you're looking to improve your operations, increase efficiency, or bring a new product to market, NAVA has the expertise and resources to help you achieve your goals. Trust us to be your partner in software and product development.

Industry

It services

Company size

51 - 200 Employees

Headquarters location

Rocky Hill, CT, US

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