R&D Machine Learning Engineer
Tasks
- Benchmark models
- Build agentic system components
- Build retrieval-augmented generation pipelines
- Collaborate cross-functional teams
- Conduct literature surveys
- Deliver technical reports
- Design machine learning algorithms
- Develop deep learning models
- Develop machine learning models
- Develop proof-of-concept systems
- Ensure model reproducibility
- Evaluate LLM based systems
- Evaluate machine learning models
- Implement ML models for R and D projects
- Manage datasets
- Optimize model efficiency
- Optimize model scalability
- Perform statistical modeling
- Plan project milestones
- Prototype LLM based components
- Run experiments
- Share knowledge and mentor engineers
- Track ML research developments
- Write technical proposals
Perks/Benefits
- Flexible working hours
- Home office equipment budget
- Inspiring office environment
- Knowledge sharing sessions
- Personal development budget
- Private health insurance
- Remote work opportunities
Skills/Tech-stack
Agentic Systems | CI/CD | Computer Vision | Containerization | Dataset Management | Deep learning | Deep learning architectures | Docker | Experiment tracking | Generative AI | Git | Language Models | Language Processing | Large Language Models | Learning architectures | Linux | MLflow | Machine Learning | Model Evaluation | Natural Language | Natural Language Processing | Optimization | Probabilistic Modeling | Python | Retrieval-Augmented Generation | Series analysis | Signal Processing | Statistical Analysis | Statistical modeling | Time Series | Time Series Analysis | Weights and Biases
Education
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