AI/NLP Data Science Engineer

Requirements:

• Proven experience developing and deploying data pipelines for AI and NLP-based search systems, including for Retrieval Augmented
• Generation (RAG) systems Strong programming skills in languages such as Python, Java, or C++
• Strong data engineering skills and experience deploying data engineering pipelines on Azure cloud platforms (3+ years experience).
• Experience with NLP information retrieval processes, including indexing, tokenizing, and hybrid search strategies.
• Proficiency in natural language processing techniques and tools (e.g., NLTK, spaCy, BERT).
• Familiarity with search technologies and platforms (e.g., Elasticsearch, Solr, Lucene).
• Ability to flex between using off-the-shelf design patterns and building custom pipelines, idepending on the given use case. Strong problem-solving skills and the ability to work both independently and as part of a team.
• Excellent communication skills and the ability to convey complex technical concepts to non-technical stakeholders.

Responsibilities:

• Design, develop, and deploy data engineering pipelines to power AI and NLP-based algorithms and systems, including Large Language Model (LLM) systems
• Collaborate with data scientists, software engineers, and product managers to understand requirements and deliver high-quality search solutions.
• Optimize search performance and scalability to handle large datasets and high query volumes.
• Stay up to date with the latest advancements in AI, NLP, and search technologies.

Our Client is a Fortune 500 company and is one of the biggest global manufacturing companies operating in the fields of industrial systems, worker safety, health care, and consumer goods. The company is dedicated to creating the technology and products that advance every business, improve every home and enhance every life.

As an AI and NLP Data Engineer, you will be responsible for developing and implementing data pipelines to power AI, LLM, and NLP algorithms. You will work closely with cross-functional teams to design, build, and optimize information retrieval solutions that deliver relevant and accurate results to our users.