AI/ML Architect

Role: AI/ML ArchitectLocation: Fremont, CADuration: Fulltime Key Responsibilities• System Design: Design end-to-end AI/ML architectures, including data ingestion, feature stores, model training pipelines, and real-time inference services.• Infrastructure & MLOps: Establish robust MLOps practices (CI/CD for ML) to automate the deployment, monitoring, and retraining of models.• Integration Specialist: Work closely with the Salesforce and Digital Engineering teams to embed AI capabilities (like Agentforce or custom LLMs) into existing business workflows.• Technical Governance: Evaluate and select third-party AI tools, frameworks, and cloud services (AWS, Azure, GCP) to ensure a future-proof tech stack.• Performance Optimization: Conduct architectural reviews to optimize model latency, throughput, and cloud infrastructure costs.Technical Requirements• Engineering Excellence: 7+ years of experience in software engineering and data architecture, with at least 3 years focused specifically on ML systems.• Cloud Architecture: Deep expertise in architecting on AWS (SageMaker), Azure (Azure ML), or Databricks.• Generative AI Stack: Proficiency in designing RAG (Retrieval-Augmented Generation) architectures, vector database selection (Pinecone, Weaviate, Milvus), and LLM orchestration (LangChain, LlamaIndex).• Data Mastery: Strong experience with Spark, Flink, or Snowflake for large-scale data processing.• Security & Compliance: Knowledge of designing systems that adhere to SOC2, GDPR, or HIPAA, especially regarding data residency and model privacy.Soft Skills• Problem Solver: The ability to take a vague business problem and decompose it into a technical blueprint.Mentor: A passion for conducting code reviews and guiding ML Engineers on best practices in system design.