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.
Read the full description and apply on the company’s own careers page.
