Senior Machine Learning Engineer
Skills
AWS SagemakerAirflowArtificial IntelligenceKubeflowMlopsMachine LearningPytorch
What the job involves
The main requirements, responsibilities and hiring steps.
Requirements
- 5+ years of professional software engineering machine-learning engineering or closely related experience
- Demonstrated experience deploying and maintaining machine-learning models in production
- Advanced proficiency with Python and common ML frameworks such as PyTorch TensorFlow or JAX
- Strong understanding of machine-learning fundamentals statistics experimentation and model evaluation
- Experience building data training and inference pipelines in a cloud environment
- Familiarity with MLOps practices including model versioning monitoring observability and automated deployment
- Strong software-engineering fundamentals including system design testing APIs and distributed systems
- Ability to operate independently in a fast-moving environment with meaningful ownership
- Clear written and verbal communication skills
Nice to have
- Startup experience
- High-growth environment
- Independent
- Owner mindset
- Clear communicator
Day to day
- Design, build and deploy machine-learning models and AI-powered product features.
- Develop scalable training, evaluation and inference pipelines for production use.
- Translate ambiguous product and business problems into practical ML solutions and improve reliability, latency, accuracy and cost efficiency.