Machine Learning Engineer, Applied AI
Bjak · Remote · Spain ·
COMPENSATION
€•• – ••k
Listed on the employer's job board (Ashby)
- Fully remote
- Python + PyTorch/JAX
- Production ML focus
- Small high-talent team
Join a team building proactive, AI-native applications for daily communication and coordination. The goal is to integrate intelligence into workflows with minimal prompting, eliminating misinformation and reducing coordination costs.
You will own the lifecycle of ML systems from development to production, solving practical problems in model quality and reliability for real users.
What you'll do
- Build and improve models for classification, ranking, retrieval and personalization
- Optimize classifier accuracy, precision, latency and cost efficiency
- Enhance search relevance using embeddings, hybrid search and reranking
- Develop personalization models that respect user privacy
- Create evaluation pipelines, labeled datasets and quality metrics
- Fine-tune existing models when sufficient data is available
- Maintain ML training, inference and deployment pipelines
- Debug production issues and monitor model performance
What you'll need
- Strong foundation in machine learning and neural architectures
- Experience deploying ML models in production environments
- Background in classification, ranking, retrieval or recommendation systems
- Understanding of model evaluation and performance metrics
- Ability to write production-quality code with real-world datasets
- Skill in balancing model quality, latency, cost and reliability
- Strong ownership and independent problem-solving abilities
Stack
- Python
- PyTorch
- JAX
- Embeddings
- Vector search
- Ranking models
Hiring process
- Technical team evaluates initial applications
- Three to four interviews conducted virtually or onsite
- Prompt decision process focused on transparency