What are the responsibilities and job description for the AI/ML Engineer position at Snowrelic Inc?
Job Description
Role: AI/ML Engineer
Duration: 3-month contract (Could be extended for 6 months before conversion)
Location: Minneapolis, MN (Remote/hybrid)
Role Objective
We are seeking a hands-on AI/ML Engineer to design, build, and deploy production-grade AI solutions. This role requires strong expertise in Generative AI, RAG (Retrieval-Augmented Generation), and enterprise integrations. The ideal candidate should be capable of independently delivering scalable AI systems aligned with business use cases.
Must-Have Skills (Non-Negotiable)
Experience building and deploying end-to-end ML/AI systems
Ability to take solutions from prototype to production
Strong prompt engineering and evaluation techniques
Experience building enterprise-grade GenAI applications
Experience with vector databases (Pinecone, Weaviate, etc.)
Ability to integrate domain-specific data into AI systems
Familiarity with orchestration frameworks and modern agent SDKs
Ability to build scalable AI services and APIs
Deploying AI solutions in cloud-native environments
Understanding of scalability, performance, and cost optimization
Infrastructure as Code (Terraform/Ansible)
Monitoring, logging, and AI observability
Nice-to-Have (Strong Plus)
Experience in education / digital learning platforms
Exposure to regulated environments
Knowledge of TypeScript / Java / SQL
Experience integrating AI into enterprise systems
Experience Required
5 years in Software Engineering / AI/ML
Proven Track Record Of
Delivering production AI systems
Working in Agile cross-functional teams
Driving solutions with minimal oversight
Role: AI/ML Engineer
Duration: 3-month contract (Could be extended for 6 months before conversion)
Location: Minneapolis, MN (Remote/hybrid)
Role Objective
We are seeking a hands-on AI/ML Engineer to design, build, and deploy production-grade AI solutions. This role requires strong expertise in Generative AI, RAG (Retrieval-Augmented Generation), and enterprise integrations. The ideal candidate should be capable of independently delivering scalable AI systems aligned with business use cases.
Must-Have Skills (Non-Negotiable)
- Core AI/ML Engineering
Experience building and deploying end-to-end ML/AI systems
Ability to take solutions from prototype to production
- Generative AI & LLMs
Strong prompt engineering and evaluation techniques
Experience building enterprise-grade GenAI applications
- RAG (Critical Requirement)
Experience with vector databases (Pinecone, Weaviate, etc.)
Ability to integrate domain-specific data into AI systems
- Agentic AI / AI Agents
Familiarity with orchestration frameworks and modern agent SDKs
- API & Backend Development
Ability to build scalable AI services and APIs
- Cloud & Deployment (GCP Preferred)
Deploying AI solutions in cloud-native environments
Understanding of scalability, performance, and cost optimization
- DevOps & Production Readiness
Infrastructure as Code (Terraform/Ansible)
Monitoring, logging, and AI observability
Nice-to-Have (Strong Plus)
Experience in education / digital learning platforms
Exposure to regulated environments
Knowledge of TypeScript / Java / SQL
Experience integrating AI into enterprise systems
Experience Required
5 years in Software Engineering / AI/ML
Proven Track Record Of
Delivering production AI systems
Working in Agile cross-functional teams
Driving solutions with minimal oversight