AI / Machine Learning Engineer

Talently is redefining how companies hire top talent across the United States and Latin America.

We believe that behind every great company is a team of exceptional people. By combining AI with expert recruiting, we help startups and scaleups find, attract, and hire the talent they need to turn ambitious ideas into reality.

Since launching, we've supported more than 500 companies and facilitated over 5,000 hires across engineering, product, data, design, and more. Today, we partner with teams that are building the future across industries.

Whether you're making your first key hire or scaling an entire organization, Talently helps you access exceptional talent faster and with greater confidence, so you can build what's next.

🤓As an AI / Machine Learning Engineer, the company expects you to perform the following tasks:

• Deploy LLM Systems: Integrate and manage practical implementations of leading LLMs via APIs (OpenAI, Anthropic, AWS Bedrock) into scalable applications.
• Build RAG Pipelines: Architect, implement, and optimize Retrieval-Augmented Generation systems to ensure accurate, context-aware AI outputs.
• Manage Vector Databases: Handle high-dimensional data, embeddings, and retrieval optimization using modern vector DBs like Pinecone, Qdrant, or Weaviate.
• Develop Agentic Workflows: Design and deploy autonomous or semi-autonomous agentic systems using LangChain, LlamaIndex, or equivalent frameworks.
• Ensure Code Quality: Write, test, and maintain robust, production-grade Python code that scales effectively under real-world user demand.

✨You are the person we are looking for if you have:

• Python Mastery: 4 to 6 years of proven experience writing clean, maintainable, production-grade Python code.
• Applied AI Experience: 2+ years of hands-on experience building, deploying, and maintaining AI/ML features in a live production environment.
• LLM Integration: Deep understanding of prompting, context window management, and API integration for major models (OpenAI, Anthropic, Bedrock).
• Data & Retrieval: Strong practical knowledge of embeddings and retrieval optimization strategies.
• Framework Proficiency: Extensive experience with modern AI orchestration frameworks (LangChain, LlamaIndex, etc.).