Machine Learning Engineer

Overview

Machine Learning Engineer to design and deploy AI-powered features for conversation intelligence, extracting meaning from voice and messaging data.

What you'll do

• Design and develop machine learning solutions for accuracy, performance, security, and scalability.
• Build and maintain end-to-end AI/ML pipelines from data ingestion to deployment.
• Instrument AI/ML services with metrics, logging, and telemetry to monitor performance and operational health against SLOs.
• Participate in on-call rotations and perform progressive rollouts and mitigations to keep inference services healthy.
• Collaborate in planning, design, and code review to contribute to product and technical discussions and improve code quality.

What you'll need

• 2+ years of experience in machine learning engineering or applied ML.
• Proficiency in Python.
• Demonstrated proficiency in at least one ML framework: PyTorch, TensorFlow, or JAX.
• Familiarity with NLP libraries such as Hugging Face Transformers, NLTK, or SpaCy.
• Experience developing, testing, and deploying small-to-medium scoped ML services/features, including model versioning, experiment tracking, and cloud infrastructure (AWS, GCP, or Azure).
• Experience using Large (or Small) Language Models within software systems.
• Excellent written and verbal communication skills for technical and non-technical audiences.

Nice to have

• Hands-on experience with conversational AI or LLM fine-tuning and prompt engineering in a production context.
• Experience with agentic AI frameworks such as LangGraph, AutoGen, or CrewAI.
• Familiarity with MLOps/LLMOps tooling for maintaining models in production (testing, versioning, model registry, retraining, monitoring).

Details

• Remote from Spain.
• May require occasional travel for in-person project or team meetings.