Senior AI/ML Engineer
Tasks
- Architect and scale retrieval augmented generation workflows
- Build tool use agent architectures
- Build vector search systems
- Collaborate with architects and stakeholders on technical strategy
- Contribute to platform reliability and cloud infrastructure initiatives
- Design and implement production ML and NLP pipelines
- Drive MLOps lifecycle for training deployment and observability
- Ensure resilient scalable ML infrastructure
- Guide ML engineering practices
- Lead research and evaluation for vector similarity search and model adaptation
- Mentor team members and review designs
Perks/Benefits
- Equity participation
- Paid Company Holidays
- Professional development opportunities
- Unlimited PTO
- Weekly in-office catering
Skills/Tech-stack
CI/CD | Cloud Architecture | Distributed Systems | Docker | Embeddings | Infrastructure as Code | Kubernetes | Language Models | Language Processing | Large Language Models | MLOps | Machine Learning | NLP | Natural Language | Natural Language Processing | Observability | Python | Retrieval-Augmented Generation | Scikit-learn | Semantic Search | Spacy | Streaming Platforms | Transformers | Vector Search | Version control | “as-code”
Education
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