ML & Data Science Engineer Remote

Propertyvalue Prudent Technologies And Consulting

San Francisco, CA, United States

about 1 month ago

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Role details

Contract type

Permanent contract

Employment type

Full-time (> 32 hours)

Experience level

Expert

Working hours

Regular working hours

Job source

www.dice.com

Tech stack

Artificial Intelligence Amazon Web Services Microsoft Azure Cloud Computing Cloud Engineering Information Engineering Data Infrastructure Machine Learning Salesforce.Com Systems Architecture Google Cloud Enterprise Software Applications

+8 more

Large Language Models Generative AI Information Technology Graphql Api Design Restful APIs Databricks Microservices

Requirements

Candidates should have 15+ years of professional experience in AI/ML engineering, data science, and enterprise technology solutions.

AI / Machine Learning / LLM Expertise

Hands-on experience with Large Language Models (LLMs)
Deep understanding of Transformer architectures
Experience with:

Retrieval-Augmented Generation (RAG) & Data Engineering

Proven experience building and scaling RAG pipelines

API Development & System Architecture

Strong understanding of:

REST APIs
GraphQL APIs
Microservices architecture

Cloud infrastructure experience:

AWS
Google Cloud Platform (Google Cloud Platform)
Microsoft Azure

Salesforce AI & Data Platform Skills

Hands-on experience with:
Salesforce Data Cloud
Salesforce Agentforce, 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.