Full-Time Data Scientist - Applied AI and Prompt Engineering

What You’ll Do

• Architect and implement production-ready AI solutions involving LLMs, transformer-based models, retrieval systems, agentic workflows, and AI agents.
• Design and iterate on prompts, workflows, and RAG pipelines.
• Design and build multi-step agentic systems that break down complex tasks.
• Deploy models and GenAI pipelines in production environments.
• Build and maintain evaluation frameworks to measure model grounding, factuality, latency, and cost.
• Develop and integrate guardrails.
• Collaborate cross-functionally with Product, Engineering, and ML Ops.

Experience:

• 3+ years applied machine learning, with hands-on focus on NLP, transformers, or generative AI systems.
• Hands-on experience with LLM-related libraries (e.g. LangChain, LlamaIndex, OpenAI API, CrewAI, or similar) and services (Azure Prompt flow, AWS Bedrock agents, or similar)
• Experience designing multi-step agents that combine LLM reasoning with tool/API calls, with safeguards against errors, loops, and unsafe tool use.
• Proven experience building and deploying machine learning models to production (API, batch, or streaming).
• Fluency in Python, with clean, modular, production-grade code practices.
• Strong ability to design and analyze ML experiments; track performance using metrics.
• Ability to develop, deploy and monitor AI-powered applications in cloud environments (e.g. AWS, Azure, GCP) using APIs, batch, or streaming architectures. Familiarity with containerization, versioning, and CI/CD.
• Experience implementing privacy, bias mitigation, safety guardrails, or related practices.

Qualifications

• Degree in Computer Science, Data Science, Engineering, or a related field (or equivalent experience).
• Expertise in transformer-based models and LLM architectures.
• Ability to bridge rapid prototyping and production deployment.
• Strong collaborator who thrives at the intersection of DS + Engineering.

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