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Remote Retrieval Augmented Generation Jobs in Secaucus, NJ

AI Engineer, Global Operations

New York, NY · On-site +1

$107K - $143K/yr

Advanced technical expertise in Python and SQL, with proven experience scaling "agentic" workflows and Retrieval-Augmented Generation (RAG) solutions using platforms like LangChain or n8n. * Proven ...

Enhance Retrieval-Augmented Generation (RAG) workflows and improve AI accuracy and reliability ... Remote-friendly, with hybrid flexibility for candidates near Chesterbrook, PA * Direct mentorship ...

Enhance Retrieval-Augmented Generation (RAG) workflows and improve AI accuracy and reliability ... Remote-friendly, with hybrid flexibility for candidates near Chesterbrook, PA * Direct mentorship ...

GenAI Product Engineering Lead

New York, NY · Remote

$104K - $138K/yr

Integrate large language models (LLMs), Retrieval-Augmented Generation (RAG), and custom agents with business processes and user-facing applications. * Lead design using frameworks such as Semantic ...

... remote. For location-specific details, please connect with our recruiting team. What you will do ... retrieval-augmented generation (RAG) pipelines that ground the agent in accurate, up-to-date ...

AI Security Architect/Partner

New York, NY · On-site +1

$71 - $92/hr

Tradeweb Technology jobs are fully remote. The Tradeweb Technology hub is in our Jersey City office ... Retrieval-Augmented Generation (RAG), and Machine Learning platforms. * Establish secure-by-design ...

AI Security Architect/Partner

New York, NY · On-site +1

$71 - $92/hr

Tradeweb Technology jobs are fully remote. The Tradeweb Technology hub is in our Jersey City office ... Retrieval-Augmented Generation (RAG), and Machine Learning platforms. * Establish secure-by-design ...

Senior Applied AI Software Engineer ( AI)

New York, NY · On-site +1

$134K - $176K/yr

I have direct experience developing AI-powered solutions, such as retrieval-augmented generation (RAG) pipelines and embeddings-based retrieval systems. These solutions also include AI agents, multi ...

Showing results 21-40

Remote Retrieval Augmented Generation information

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 skills and qualifications are needed to thrive as a remote retrieval augmented generation engineer?

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 are 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 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 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:

Applied AI Engineer - Enterprise Solutions

Snorkel AI

New York, NY • On-site, Remote

Full-time

Re-posted 9 days ago


Job description

About Snorkel
At Snorkel, we believe meaningful AI doesn't start with the model, it starts with the data.
We're on a mission to help enterprises transform expert knowledge into specialized AI at scale. The AI landscape has gone through incredible changes since 2015, when Snorkel started as a research project in the Stanford AI Lab, to the generative AI breakthroughs of today. But one thing has remained constant: the data you use to build AI is the key to achieving differentiation, high performance, and production-ready systems. We work with some of the world's largest organizations to empower scientists, engineers, financial experts, product creators, journalists, and more to build custom AI with their data faster than ever before. Excited to help us redefine how AI is built? Apply to be the newest Snorkeler!
The Role
As an Applied AI Engineer, you'll research and utilize state-of-the-art Gen AI and machine learning (ML) techniques to successfully deliver solutions to our customers. You will work directly with our customers to understand their business and technical needs and design and deliver AI solutions to solve them. You will also help define Snorkel's Applied AI tooling by translating repeatable real-world challenges into reusable solution recipes, workflows, best practices, and platform-level capabilities that become part of Snorkel's next generation of AI tooling. We move fast and are constantly prototyping and innovating new ways to deliver value to our customers. This position is ideal for someone who enjoys solving complex problems, bridging the gap between AI technology and business value, working directly with customers, keeping up-to date with AI research, and standardizing bespoke solutions into internal recipes and staying naturally curious about the infrastructure that underpin the Applied AI stack end-to-end.
Main Responsibilities
  • Partner with customers to build and deploy impactful Gen AI and machine learning solutions, from use case scoping and data exploration to model development and deployment. This will involve designing custom approaches using state-of-the-art tools, with the goal of delivering real business value and informing the evolution of Snorkel's tooling.
  • Develop and implement state of the art AI systems such as retrieval-augmented generation (RAG), fine-tuning pipelines, prompt engineering recipes and agentic workflows.
  • Create augmented real-world datasets and comprehensive evaluation workflows to ensure model reliability, transparency, and stakeholder trust. A data- and evaluation-first mindset is essential for success in this role.
  • Forge and manage relationships with our customers' leadership and stakeholders to ensure successful development and deployment of AI projects.
  • Collaborate closely with pre-sales Solutions and Product teams to map customer needs to existing capabilities, prioritize roadmap gaps, and guide successful project setup.
  • Work with other Applied AI Engineers to standardize solutions and contribute to internal tooling and best practices.
  • Lead stakeholder education on quantitative capabilities, helping them to understand the strengths and weaknesses of different approaches and what problems are best-suited for Snorkel AI.
  • Serve as the voice of our customers for new AI paradigms, data science workflows, and share customer feedback to product teams.
  • Conduct one-to-few and one-to-many enablement workshops to transfer knowledge to customers considering or already using Snorkel AI.
  • Annual travel up to 25%.
Preferred Qualifications
  • B.S. degree in a quantitative field such as Computer Science, Engineering, Mathematics, Statistics, or comparable degree/experience.
  • 3+ years of customer-facing experience in the design and implementation of AI/ML solutions.
  • Proficiency in Python, including strong grounding in software engineering fundamentals (e.g., modular design, testing, profiling, packaging) and experience with modern Python constructs and libraries for type validation and typed data modeling (e.g., pydantic), building type-safe systems (e.g., mypy), testing (e.g., pytest), packaging and environment configuration (e.g., poetry), API and service frameworks (e.g., FastAPI), serialization and structured data handling (e.g., msgspec), and orchestration tooling relevant to ML deployment (e.g., Ray, Airflow).
  • Expertise across the Applied AI stack, spanning classical ML libraries (e.g., scikit-learn), deep learning frameworks (e.g., PyTorch), foundation-model ecosystems (e.g., Hugging Face Transformers), vector/embedding tooling (e.g., FAISS), data processing frameworks (e.g., pandas, Spark), retrieval/RAG tooling (e.g., Chroma, Weaviate), synthetic dataset curation, evaluation workflows, and LLM orchestration, workflow, agent authoring tools (e.g., LlamaIndex, LangGraph, CrewAI).
  • Experience leading strategic, customer-facing initiatives and collaborating with business stakeholders to ensure ML solutions drive successful business outcomes, with a strong focus on teaching and enablement.
  • Outstanding presentation skills to technical and executive audiences, whether impromptu on a whiteboard or using presentations and demos.
  • Ability to work in a fast-paced environment and balance priorities across multiple projects at once.

Compensation range for Tier 1 locations of San Francisco Bay Area $172K - $300K OTE. All offers also include equity in the form of employee stock options. Our compensation ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training.
Locations
San Francisco, CA - Hybrid - US; New York, NY - Hybrid
#LI-CG1
Actual compensation will be determined based on factors including skills, qualifications, experience, and geographic location.
Salary range(s) for this role
$175,000-$300,000 USD
Be Your Best at Snorkel
Joining Snorkel AI means becoming part of a company that has market proven solutions, robust funding, and is scaling rapidly-offering a unique combination of stability and the excitement of high growth. As a member of our team, you'll have meaningful opportunities to shape priorities and initiatives, influence key strategic decisions, and directly impact our ongoing success. Whether you're looking to deepen your technical expertise, explore leadership opportunities, or learn new skills across multiple functions, you're fully supported in building your career in an environment designed for growth, learning, and shared success.
Snorkel AI is proud to be an Equal Employment Opportunity employer and is committed to building a team that represents a variety of backgrounds, perspectives, and skills. Snorkel AI embraces diversity and provides equal employment opportunities to all employees and applicants for employment. Snorkel AI prohibits discrimination and harassment of any type on the basis of race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local law. All employment is decided on the basis of qualifications, performance, merit, and business need.
We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.