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Thaloz

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Thaloz is a tech consulting and outsourcing company focused on cloud-native product development and engineering team outsourcing. They offer tailored software development solutions, leveraging top-tier talent from Latin America. Thaloz provides a variety of services such as custom product development, staff augmentation, and enterprise solutions. Their approach emphasizes people-focused consulting and remote work culture, ensuring seamless integration of skilled IT professionals into their clients' projects. With expertise in diverse technologies, Thaloz offers end-to-end support from strategy to launch, fostering smooth communication and collaboration.

Staff Augmentation • Remote jobs • IT Recruitment • consultancy • IT Consultancy

51 - 200 employees

☁️ SaaS

🤝 B2B

🏢 Enterprise

📋 Description

• We are looking for a talented and innovative Large Language Model (LLM) Engineer with specialized experience in Retrieval Augmented Generation (RAG) to join our dynamic team. • The ideal candidate will be instrumental in the development, optimization, and deployment of RAGbased LLM solutions that meet various business needs. • This role requires a deep understanding of Data Science, Machine Learning (ML), Natural Language Processing (NLP), and the fundamentals of LLMs. • The successful candidate will have hands-on experience with agent based prompting techniques such as LangChain, APIdriven development architectures for AI products, usage of vector databases, and information retrieval pipelines to extract actionable insights. • Additionally, strong listening skills and an ability to understand business requirements are essential for designing effective solutions tailored to stakeholder needs. • Job Responsibilities: Develop robust RAGbased LLM solutions that enhance data retrieval processes while ensuring high quality output aligned with business objectives. • Craft effective prompts that efficiently guide LLMs towards generating outputs that fulfill specific business requirements; iterate on prompt designs based on performance metrics. • Design, develop, and refine AI products based on user feedback and stakeholder requirements; ensure alignment with program priorities through agile methodologies. • Collaborate closely with ML engineering teams during the deployment phase of APIs in production environments; assist in troubleshooting issues related to model performance or integration challenges. • Document Generative AI use cases comprehensively; create manuals detailing workflows, methodologies employed in solution design, and best practices adopted throughout the process. • Develop and maintain RAG concepts following established data science principles; ensure adherence to industry standards while fostering innovation. • Ensure efficient operation of data pipelines and processes according to company security policies; promote Responsible AI practices within all project phases. • Work closely with cross functional teams including product managers, data scientists, software engineers, and stakeholders to align goals effectively; communicate technical concepts clearly across diverse audiences.

🎯 Requirements

• A minimum of 3 years' experience working with Python for machine learning applications along with expertise in AWS Cloud Computing services. • Familiarity with AWS Bedrock's suite of LLM models along with associated prompting strategies tailored for optimal performance. • At least 1 year of direct experience working specifically within NLP frameworks/LLMs focusing on Retrieval Augmented Generation models. • Proficiency in Python programming language utilized extensively for data science projects involving AI development. • Familiarity with agent based frameworks like LangChain which support advanced interactions between users/models. • Experience leveraging AI training frameworks such as TensorFlow or PyTorch alongside Hugging Face Transformers library for model building/training tasks. • Demonstrated expertise in prompt engineering techniques aimed at finetuning large language models tailored toward specific applications or industries. • Knowledgeable about vector databases including practical experience implementing embedding techniques necessary for enhanced information retrieval capabilities.