Job description

Company Description

Blend is a premier AI services provider, committed to co-creating meaningful impact for its clients through the power of data science, AI, technology, and people. With a mission to fuel bold visions, Blend tackles significant challenges by seamlessly aligning human expertise with artificial intelligence. The company is dedicated to unlocking value and fostering innovation for its clients by harnessing world-class people and data-driven strategy. We believe that the power of people and AI can have a meaningful impact on your world, creating more fulfilling work and projects for our people and clients. For more information, visit www.blend360.com

Job Description

We’re looking for a Lead Data Scientist specialized in Generative AI to spearhead the development and deployment of cutting-edge AI solutions that power intelligent recommendation systems and personalized user experiences. In this role, you’ll lead initiatives leveraging LLMs, embeddings, and GenAI frameworks, while also shaping the technical direction of our AI strategy.

You may work 100% remotely from Colombia, Uruguay, Argentina or Chile, or come to our offices in Montevideo or Bogotá, its up to you!

In this role you will

Lead the design and deployment of Generative AI models, including LLMs and multi-modal architectures, for personalized content and recommendations.
Drive the development of end-to-end machine learning pipelines, from data preprocessing to production deployment.
Implement scalable MLOps practices, ensuring robust monitoring, CI/CD, and model lifecycle management.
Collaborate with cross-functional teams to align business goals with advanced ML and GenAI solutions.
Mentor and guide junior data scientists and ML engineers, fostering innovation and best practices.
Translate complex technical concepts into actionable insights for both technical and non-technical stakeholders.

Qualifications

5+ years in data science or machine learning roles, with at least 2 years in GenAI or NLP-focused projects.
Strong experience building and fine-tuning LLMs (e.g., GPT, LLaMA, Claude) or using RAG pipelines.
Proficient in Python and libraries such as Transformers, LangChain, Scikit-learn, PyTorch, or PyMC.
Hands-on experience with MLOps tools (e.g., MLflow, Vertex AI, SageMaker) and deploying models at scale.
Deep understanding of machine learning theory, embeddings, and recommendation systems.
Experience with cloud platforms (AWS, Azure, GCP) and distributed data processing (e.g., Spark, Databricks) is a strong plus.
Strong communication skills and leadership ability to influence technical direction and decision-making.