Staff Engineer - Data Scientist

Posted 13 Hours Ago
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Hiring Remotely in USA
Remote
Mid level
Artificial Intelligence • Information Technology • Machine Learning • Software • Virtual Reality • Analytics
The Role
The Staff Engineer - Data Scientist will leverage Python and various machine learning techniques to develop AI-driven solutions. Responsibilities include training Foundation Models, working with LLM APIs, managing knowledge graphs, and applying natural language processing to unstructured data. Candidates should also have a solid understanding of multi-agent systems and RAG concepts.
Summary Generated by Built In

Company Description

We are a Digital Product Engineering company that is scaling in a big way! We build products, services, and experiences that inspire, excite, and delight. We work at scale — across all devices and digital mediums, and our people exist everywhere in the world (19000+ experts across 33 countries, to be exact). Our work culture is dynamic and non-hierarchical. We are looking for great new colleagues. That is where you come in!

Job Description

  • Proficiency in Python and all associated DS libraries and frameworks.
  • Strong knowledge in AI, machine learning, and natural language processing.
  • Experience with leveraging, training and fine-tuning Foundation Models, including multimodal inputs and outputs.
  • Strong experience working with key LLM models APIs (e.g. OpenAI, Anthropic) and LLM Frameworks (e.g. LangChain, LlamaIndex).
  • Experience with multi-agent frameworks/systems and an understanding of multi-agent systems and their applications in complex problem-solving scenarios.
  • Experience with unstructured.io or similar libraries for handling various document formats and extracting structured information from unstructured data.
  • Expertise in using Llama Index for building and querying knowledge bases, including its data connectors, indexing strategies, and query engines.
  • Knowledge of effective text chunking techniques for optimal processing and indexing of large documents or datasets.
  • Proficiency in generating and working with text embeddings using models like BERT, GPT, or domain-specific embedding models.
  • Understanding of embedding spaces and their applications in semantic search and information retrieval.
  • Experience in constructing and querying knowledge graphs, including technologies like Neo4j or RDF triplestores.
  • Understanding of ontology design and graph-based reasoning.
  • Experience with RAG concepts and fundamentals (vectorDBs, semantic search, etc.).
  • Expertise in implementing RAG systems that combine knowledge bases with generative AI models.
  • Proficiency in Python and all associated DS libraries and frameworks.
  • Strong knowledge in AI, machine learning, and natural language processing.
  • Experience with leveraging, training and fine-tuning Foundation Models, including multimodal inputs and outputs.
  • Strong experience working with key LLM models APIs (e.g. OpenAI, Anthropic) and LLM Frameworks (e.g. LangChain, LlamaIndex).
  • Experience with multi-agent frameworks/systems and an understanding of multi-agent systems and their applications in complex problem-solving scenarios.
  • Experience with unstructured.io or similar libraries for handling various document formats and extracting structured information from unstructured data.
  • Expertise in using Llama Index for building and querying knowledge bases, including its data connectors, indexing strategies, and query engines.
  • Knowledge of effective text chunking techniques for optimal processing and indexing of large documents or datasets.
  • Proficiency in generating and working with text embeddings using models like BERT, GPT, or domain-specific embedding models.
  • Understanding of embedding spaces and their applications in semantic search and information retrieval.
  • Experience in constructing and querying knowledge graphs, including technologies like Neo4j or RDF triplestores.
  • Understanding of ontology design and graph-based reasoning.
  • Experience with RAG concepts and fundamentals (vectorDBs, semantic search, etc.).
  • Expertise in implementing RAG systems that combine knowledge bases with generative AI models.

Qualifications

Must have Skills: Python for Data Science (Capable).\

Good To Have Skills: Machine Learning on AWS (Capable), Generative AI Fundamentals (Capable).

Top Skills

Python
The Company
19,994 Employees
On-site Workplace
Year Founded: 1996

What We Do

Nagarro helps future-proof your business through a forward-thinking, fluidic, and CARING mindset. We excel at digital engineering and help our clients become human-centric, digital-first organizations, augmenting their ability to be responsive, efficient, intimate, creative, and sustainable. Today, we are 19,000 experts across 36 countries, forming a Nation of Nagarrians, ready to help our customers succeed.

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