Technisch Engineer.

Wizeline; Chantada; Presencial; EUR 65.000 - 90.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

High-Impact Environment

Professional Development

Flexible and Collaborative Culture

Global Opportunities

Vibrant Community

Total Rewards

Descripción de la vacante

Wizeline, a global AI-native technology solutions provider, is seeking an experienced ML/Data Engineer to orchestrate LLM-driven AI workflows and build scalable data pipelines. You will collaborate with data scientists and engineers to deploy LLMs, optimize NLP vector storage, and extend LangChain-based tools across teams.

The role emphasizes hands-on development, cloud infrastructure familiarity, and building observability into ML solutions while staying current with GenAI and NLP innovations.

Formación

• Bachelor's or Master's in CS/Engineering/Data Science or 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 used in ML.
• Experience deploying LLMs and building multi-agent systems with tool-calling and memory.

Responsabilidades

• Collaborate with data scientists and engineers to orchestrate LLMs and tools into AI workflows.
• Implement optimized vector storage and indexing for NLP.
• Develop tools/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 large data volumes.

Conocimientos

Python

ML Engineering

Data Engineering

LLM Deployment

Multi-agent systems

Cloud Infrastructure

API integration

Educación

Bachelor's/Master's in CS/Engineering/Data Science or related field

Herramientas

LangChain

Docker

AWS/GCP

Git

Descripción del empleo

Descripción del trabajo

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.