- Company Name
- Relanto
- Job Title
- AI/ML Lead/Architect
- Job Description
-
**Job Title:** AI/ML Lead/Architect
**Role Summary:**
Lead end‑to‑end AI/ML architecture and delivery of production systems that combine traditional machine learning models with agentic AI capabilities. Drive solutions in seller enablement and customer intelligence (segmentation, propensity, cross‑sell/upsell, win‑probability, churn) and oversee modeling, orchestration, tooling, and guardrails. Act as technical liaison between distributed engineering teams (US & India) and executive stakeholders.
**Expectations:**
- Own architectural design and technical delivery of AI/ML pipelines from data ingestion to production.
- Validate and deploy models that meet business performance metrics.
- Champion best practices for agentic AI, including planner/executor orchestration, function calling, NL2SQL, RAG, and guardrails.
- Communicate complex concepts clearly to technical and non‑technical audiences.
**Key Responsibilities:**
- Design, develop, and production‑grade ML models (boosting, ensembles, logistic regression, tree‑based) for segmentation, propensity, cross‑sell/upsell, win‑probability, churn.
- Architect and implement agentic AI workflows: orchestrating autonomous agents for data extraction, NL2SQL queries, RAG pipelines, and function calls.
- Integrate with cloud AI/ML platforms (e.g., GCP Vertex AI, Gemini) and ensure model serving, scaling, and monitoring.
- Write architecture and design documentation, model rollback plans, and guardrail strategies.
- Lead technical discussions, code reviews, and architecture talks with distributed teams.
- Present results, insights, and ROI to executives and cross‑functional stakeholders.
**Required Skills:**
- Proficiency in traditional ML algorithms: boosting, ensemble methods, logistic regression, tree‑based models.
- Deep expertise in agentic AI: agent orchestration, planning/executing, function calling, NL2SQL, RAG, and guardrails.
- Experience with cloud AI/ML services (GCP Vertex AI, Gemini, or equivalent).
- Strong programming in Python, SQL, and familiarity with ML Ops tooling.
- Excellent written and verbal communication; ability to translate technical details for business audiences.
- Experience leading distributed teams and coordinating across multiple time zones.
**Required Education & Certifications:**
- Bachelor’s or Master’s degree in Computer Science, Data Science, Machine Learning, or related field.
- Preferred Certifications: Google Professional Data Engineer, Google Professional Machine Learning Engineer, or equivalent AWS/GCP/Azure ML certifications.
Santa clara, United states
Hybrid
Senior
19-02-2026