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Role: AI/ML Architect (Locals Only – SFO Bay Area, CA)
Location: San Francisco Bay Area, CA (Hybrid – 2–3 days onsite)
Experience: 13–16 Years
Job Type: Contract/W2
Duration: Long Term
Rate (C2C): $90/hr
⚠️ Candidates must be local to the San Francisco Bay Area and available for hybrid onsite work. Non-local profiles will not be considered.
Candidates must have strong experience in customer segmentation using data science and machine learning techniques
Role Summary
RelantoAI is seeking a highly experienced, hands-on AI/ML Architect to design, build, and scale production-grade AI and ML solutions for enterprise clients. This role will own end-to-end AI/ML architecture, collaborate with cross-functional teams, and drive scalable ML platform implementations.
Key Responsibilities
- Architect and design end-to-end AI/ML and Generative AI solutions
- Build scalable ML platforms and define MLOps frameworks (training, deployment, monitoring, governance)
- Lead customer segmentation and advanced analytics initiatives using ML models
- Collaborate with data engineering teams on pipelines, feature stores, and data quality frameworks
- Translate business use cases into AI/ML system architecture
- Deploy ML models into production with monitoring, drift detection, and performance tracking
- Provide technical leadership, conduct architectural reviews, and mentor engineering teams
- Work directly with client stakeholders in a consulting-facing environment
Required Qualifications
- 13+ 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, GCP, 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.
Looking forward to qualified local submissions only.
Thanks & Regards,
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