Principal Applied AI/ML Engineer
Tasks
- Define AI solution strategy across build evaluate secure monitor
- Design LLM ML pipelines and retrieval systems
- Design cross regional distributed systems for latency availability failover
- Design relational and graph database systems
- Drive cloud architecture decisions on AWS
- Establish engineering best practices with automated testing validation QA release discipline
- Lead architecture of production AI systems
- Provide technical leadership through mentoring and design reviews
- Translate business needs into technical roadmaps and execution plans
Perks/Benefits
- Continuous learning opportunities
- Flexible work arrangements
- Health benefits (medical, dental, vision)
- Inclusive workplace culture
- Mentorship
- Professional development
- Work-life balance
Skills/Tech-stack
API Development | AWS | Agentic Workflows | Automated testing | Cost Optimization | Data Modeling | Database performance | Database performance tuning | Deep learning | Distributed Systems | Failover | Graph Databases | LLM Agents | Language Models | Large Language Models | Latency optimization | Machine Learning | Microservices | Observability | Performance Tuning | Python | QA processes | Relational databases | Reliability Engineering | Retrieval-Augmented Generation | Scalability | Schema Design | Security
Education
N/A
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