Senior ML Engineer_ Remote (Full-Time)

Senior ML Engineer_ Remote

FULL TIME

Preferred candidates are located on the West Coast.

Note: Candidates should be available for occasional business travel as needed.

KEY REQUIREMENTS & QUALIFICATIONS

• Technical Stack & Engineering Expertise
• Programming Languages: Expert-level fluency in Python and SQL; proficiency in modern JavaScript/TypeScript or Apex is a strong plus.
• AI/ML & LLM Architectures: Deep hands-on experience with Large Language Models, transformer architectures, vector databases (e.g., Pinecone, Milvus, pgvector), embedding models, and multi-agent orchestration frameworks (e.g., LangChain, LlamaIndex, Semantic Kernel).
• RAG & Data Pipelines: Proven track record of designing, building, and scaling advanced RAG pipelines, chunking strategies, semantic caching, and real-time ETL data pipelines.
• API & System Integration: Deep understanding of REST/GraphQL APIs, microservices architectures, OAuth/security protocols, and cloud infrastructure (AWS, Google Cloud Platform, or Azure).
• Platform & Ecosystem Knowledge
• Salesforce Ecosystem: Deep familiarity and hands-on experience with core Salesforce architecture (Sales/Service Cloud, Apex, Lightning Web Components).
• Advanced Salesforce AI & Data Stacks: Mastery of Salesforce Data Cloud (Customer Data Platform) and Agentforce, understanding how to leverage unified data models for contextual AI actions.

PREFERRED QUALIFICATIONS

• Advanced Degree: M.S. or Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related quantitative field.
• Prior FDE Experience: Previous experience as a Forward Deployed Engineer, Solutions Architect, or Principal ML Engineer in high-growth enterprise SaaS or AI-first companies (e.g., Palantir, Databricks, OpenAI enterprise practices).
• Certifications: Salesforce Certified AI Specialist, Data Cloud Consultant, or equivalent cloud architecture certifications.