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Tech Stack
Tools & technologiesCloudNode.jsPythonPyTorchTensorflow
About the role
Key responsibilities & impact- Design and deploy sophisticated reasoning and swarm agents
- Develop algorithms for automated node-level optimization
- Build hybrid agentic search systems
- Engineer cloud-based pipelines and A/B testing frameworks
- Own the end-to-end MLOps process
- Identify ML opportunities and propose solutions
Requirements
What you’ll need- 3+ years of experience researching, developing and deploying production-grade ML systems
- Expertise in deep learning, NLP, Information Retrieval, and recommender systems using frameworks like PyTorch or TensorFlow
- Proven track record of building and evaluating LLM-powered products
- Expertise in RAG architectures, agentic frameworks, and long-context LLM applications
- Expert-level Python skills
- Hands-on experience with the full ML lifecycle including model fine-tuning and cloud-native deployment
Benefits
Comp & perks- Workday Bonus Plan
- Annual refresh stock grants
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
machine learningdeep learningnatural language processinginformation retrievalrecommender systemsPyTorchTensorFlowPythonMLOpsmodel fine-tuning
