Applied Machine Learning Engineer
Bjak · Remote · China ·
COMPENSATION
€•• – ••k
Listed on the employer's job board (Ashby)
- Fully remote
- Python + PyTorch/JAX
- Production ML focus
- Small high-impact team
Join a mission to build proactive, AI-native applications for daily communication and workflows. The team is developing an agent-first mobile app that integrates intelligence into conversations and tasks with minimal prompting.
As an Applied Machine Learning Engineer, you will own the lifecycle of ML systems from development to production. You will solve practical problems in model quality, reliability and efficiency for real-world users.
What you'll do
- Build and improve ML models for classification, ranking, retrieval and personalization
- Optimize classifier accuracy, precision, latency and cost efficiency
- Enhance search relevance using embeddings, hybrid search and reranking techniques
- Develop personalization models that learn from user behavior while preserving privacy
- Create evaluation pipelines, labeled datasets and metrics for model quality
- Fine-tune existing models when sufficient data is available
- Maintain ML training, inference and deployment pipelines
- Debug production issues and monitor performance based on real-world feedback
What you'll need
- Strong foundation in machine learning and modern neural architectures
- Hands-on experience deploying ML models in production environments
- Background in classification, ranking, retrieval or recommendation systems
- Understanding of model evaluation, experimentation and performance metrics
- Ability to write production-quality code and handle real-world datasets
- Skill in balancing model quality, latency, cost and reliability
- Strong ownership mindset and problem-solving capabilities
Stack
- Python
- PyTorch
- JAX
- Embeddings
- Vector search
- Ranking models
How you'll work
- Remote work environment
- Virtual and/or onsite interviews
- Small, hands-on team structure
- Collective decision-making process
Hiring process
- Technical team evaluates applications
- Three to four interviews maximum
- Interviews conducted virtually or onsite
- Prompt decision following final interview