Machine Learning Engineer (AI)

Related skills

📋 Description

• Build and own production-grade ML/AI systems end-to-end.
• Develop LLM, RAG, conversational AI, and agentic workflows.
• Work on personalization, memory, recommendations, and user intelligence.
• Build LLM orchestration, evaluation, and optimization systems for quality, latency, and cost.
• Combine structured astrology intelligence with ML, retrieval, and LLM reasoning.
• Work closely with Product, Backend, and other teams to ship impactful features at scale.

🎯 Requirements

• 3–5 years in ML, Applied ML, NLP, or GenAI engineering.
• Strong Python and software engineering fundamentals.
• Hands-on experience with LLMs, RAG, embeddings, vector search, or conversational AI.
• Experience deploying ML/AI systems to production.
• Strong understanding of ML fundamentals, evaluation, APIs, system design, scalability, and cloud.
• Ability to own problems end-to-end: design → build → evaluate → production.

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