AI / ML Architect

2 months ago


Auburn Hills, United States Marvel Technologies Inc Full time

Role: AI / ML Architect

Location: Auburn Hills, MI / Onsite

Duration: Long Term

Job Summary:

We are seeking an experienced AI/ML Architect to design and develop conversational AI solutions using Retrieval-Augmented Generation (RAG) techniques. The ideal candidate will have a strong background in natural language processing (NLP), machine learning, and software architecture, with expertise in building scalable and efficient conversational AI systems. The AI/ML Architect will work closely with cross-functional teams to develop AI-powered chatbots that leverage company documents and data to provide accurate and informative responses.

Key Responsibilities:

- Design and implement conversational AI architectures using RAG techniques

- Develop and train machine learning models for NLP tasks such as text classification, entity recognition, and language generation

- Integrate company documents and data into the conversational AI system

- Collaborate with software engineers to develop scalable and efficient software applications

- Conduct experiments and evaluations to improve the performance and accuracy of the conversational AI system

- Stay up-to-date with the latest advancements in NLP, machine learning, and conversational AI

Requirements:

- Master's degree in Computer Science, AI/ML, or related field

- 5+ years of experience in AI/ML, with a focus on NLP and conversational AI

- Strong understanding of RAG techniques and their applications in conversational AI

- Experience with deep learning frameworks such as TensorFlow or PyTorch

- Knowledge of software architecture and design patterns

- Excellent problem-solving and analytical skills

- Strong communication and collaboration skills

- Relevant certifications (e.g., Certified Data Scientist) a plus

Nice to Have:

- Experience with cloud-based AI/ML platforms (e.g., AWS SageMaker, Google Cloud AI Platform)

- Knowledge of graph-based neural networks and their applications in NLP

- Familiarity with DevOps practices and tools (e.g., Docker, Kubernetes)

- Experience with agile development methodologies



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