AI Engineer
Role details
Job location
Tech stack
Job description
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Develop and maintain existing AI pipeline (neural network, machine learning, LLM, etc.) to expand its capabilities, enable reliable knowledge retrieval & reasoning, and incorporate state-of-the-art technologies to further automate tasks and expand on the clients' overall operational improvements. o Specific focus on the machine learning and large language model disciplines is a requirement
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Design and implement robust models, within the Maestro AI pipeline, and experiment with new approaches to support performance and KPI optimization.
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Design and implement agent-based workflows to support KPI analysis, performance monitoring, and multi-step analytical reasoning across data and models.
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Build and iterate-on efficient, maintainable prototypes, rigorously evaluate model performance from both statistical and business perspectives, and deploy scalable solutions to the production environment.
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Collaborate closely with in-house Domain Engineers to solve industrial/business problems utilizing the Maestro AI pipeline.
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Play a key role in communicating complex technical concepts clearly to non technical stakeholders.
Requirements
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Master's degree in Computer Science, Artificial Intelligence, Electrical Engineering, Computer Engineering, Statistics, or a related field, with preferably 1-3 years of experience developing AI or machine learning algorithms or technologies, but we will accept candidates who are newly graduated as well.
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Proficiency in Python and SQL, with hands-on experience using deep learning frameworks such as PyTorch or TensorFlow.
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Familiarity with MLOps processes supporting the full lifecycle from model development to deployment in production environments.
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Experience in data science with machine learning algorithms and applying them in line with industry best practices.
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Experience building or working with large language model (LLM) applications, including retrieval-augmented generation (RAG) systems, with proficiency in LLM frameworks such as LangChain and LlamaIndex.
Benefits & conditions
There will be three interviews for the most qualified candidates:
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Introduction - Candidates will interview with Department Leadership and AI Engineering team members to assess whether they are fits within Elutions' culture and the AI Engineering Team;
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Technical Assessment - AI Engineering leadership will administer an in person or virtual technical test to assess whether the candidate has the requisite technical knowledge and skills to be brought onto the team; a. Should Elutions' Leadership not be satisfied with the outcome of the test then they can elect to administer a take home test for further assessment;
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Offer Package Issuance - Following the first two interviews the candidate will be notified whether they are eligible for the position and will be issued an Offer Package for their consideration. Any questions will be directed to the Department Head for swift responses and execution of the agreement.