Summary: Collaborate with data scientists and engineers to orchestrate LLMs and tools into complex AI workflows, building and maintaining data processing pipelines for high volumes of structured and unstructured data. Highlights: 1. Develop cutting-edge, AI-powered digital products and platforms 2. Global community of innovators fostering growth and collaboration 3. High-impact environment with commitment to professional development **We are:** Wizeline, a global AI\-native technology solutions provider, develops cutting\-edge, **AI\-powered** digital products and platforms. We partner with clients to leverage data and AI, accelerating market entry and driving business transformation. As a global community of innovators, we foster a culture of **growth, collaboration,** and **impact.** **With the right people and the right ideas, there’s no limit to what we can achieve** **Are you a fit?** Sounds awesome, right? Now, let’s make sure you’re a good fit for the role: ***Key Responsibilities*** * Collaborate with data scientists and engineers to orchestrate LLMs and tools into complex AI workflows. * Implement optimized vector storage and indexing systems for NLP. * Develop tools and frameworks for prompt management, automated evaluations, and observability. * Monitor and improve agentic systems performance for accuracy and efficiency. * Provide ongoing support, troubleshoot issues, and implement updates for ML solutions * Build and maintain data processing pipelines for high volumes of structured and unstructured data. * Integrate third\-party AI APIs (internal and external) to extend the functionality of systems. * Stay updated on GenAI, NLP, ML, and IR technologies, incorporating best practices and leveraging cloud infrastructure for efficiency. * Build and extend internal products on top of the LangChain ecosystem (LangGraph, LangSmith) to support prompt management, evaluation, and agent orchestration across the team. ***Must\-have Skills:*** * Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related STEM field or equivalent work experience. * 4\+ years of industrial experience in a machine learning engineering or data engineering role. * Strong programming skills in Python and/or another high\-level language commonly used in machine learning. * Experience deploying LLMs, implementing automated evaluation pipelines (LLM\-as\-a\-judge), and architecting multi\-agent systems that utilize tool\-calling and long\-term memory to solve non\-linear problems. ***Nice\-to\-have:*** * **AI Tooling Proficiency**: Leverage one or more AI tools to optimize and augment day\-to\-day work, including drafting, analysis, research, or process automation. Provide recommendations on effective AI use and identify opportunities to streamline workflows. * Familiarity with cloud\-based infrastructure and services (e.g., AWS and GCP), Docker, and the Git version control system * Familiarity with consuming and integrating APIs in a reliable and secure manner. **What we offer:** * A High\-Impact Environment * Commitment to Professional Development * Flexible and Collaborative Culture * Global Opportunities * Vibrant Community * Total Rewards * *Specific benefits are determined by the employment type and location.* Find out more about our culture here.
David Muñoz
Indeed · HR
David Muñoz
Indeed · HR
