What are the responsibilities and job description for the AI/ML Architect position at Jobs via Dice?
Dice is the leading career destination for tech experts at every stage of their careers. Our client, Relanto, Inc., is seeking the following. Apply via Dice today!
Role: AI/ML Architect
Location: Fremont, CA (Hybrid)
Duration: Full-time
Job Description:
We are seeking an experienced and visionary AI/ML Architect to lead the end-to-end design, development, deployment, and operationalization of advanced AI/ML and Generative AI (GenAI) solutions on cloud platforms. The ideal candidate will possess deep technical expertise in ML architecture, GenAI frameworks, Retrieval-Augmented Generation (RAG) pipelines, cloud-native deployment, and MLOps practices. You will work closely with cross-functional teams, clients, and engineering teams to define scalable AI strategies and deliver cutting-edge solutions across various domains.
Required Qualifications
Role: AI/ML Architect
Location: Fremont, CA (Hybrid)
Duration: Full-time
Job Description:
We are seeking an experienced and visionary AI/ML Architect to lead the end-to-end design, development, deployment, and operationalization of advanced AI/ML and Generative AI (GenAI) solutions on cloud platforms. The ideal candidate will possess deep technical expertise in ML architecture, GenAI frameworks, Retrieval-Augmented Generation (RAG) pipelines, cloud-native deployment, and MLOps practices. You will work closely with cross-functional teams, clients, and engineering teams to define scalable AI strategies and deliver cutting-edge solutions across various domains.
Required Qualifications
- 7 years of overall IT experience, with minimum of 5 years in designing, developing, deploying, and operationalizing AI/ML solutions.
- Minimum 2–3 years of experience in architecting end-to-end AI/ML solutions, including design, implementation, and production deployment.
- Proven experience in GenAI, LLMs, RAG architecture, prompt engineering, and orchestration tools like LangChain, LlamaIndex, etc.
- Hands-on with vector databases (e.g., Pinecone, FAISS, Elasticsearch) and unstructured data retrieval.
- Deep knowledge of Machine Learning and Deep Learning algorithms: CNNs, RNNs, LSTMs, Transformers, etc.
- Experience in Natural Language Processing (NLP), including language modeling, summarization, classification, and NER.
- Strong expertise in Python, with frameworks like PyTorch, TensorFlow, HuggingFace, NumPy, and Pandas.
- Demonstrated experience in designing cloud-native AI/ML solutions on AWS, Google Cloud Platform, or Azure.
- Skilled in deploying models via services like SageMaker, Vertex AI, Azure ML, or using containers and Kubernetes.
- Solid understanding of MLOps/LLMOps lifecycle: pipeline automation, model registry, monitoring, CI/CD.
- Excellent communication, leadership, and stakeholder management skills.
- Certification in AWS/Google Cloud Platform or ML specializations.
- Experience in leading large-scale AI transformation programs.