Machine Learning Engineer
Tasks
- Build MLOps workflows with CI CD
- Build data pipelines
- Design feature engineering pipelines
- Develop training and inference workflows
- Ensure model lifecycle automation
- Execute offline and online validation
- Implement vector search
- Improve LLM workflows with retrieval augmented generation
- Integrate models into scalable product architectures
- Monitor ML systems for drift latency and accuracy
- Operationalize machine learning models
- Perform debugging and failure analysis
- Run experiment design and model tuning
- Serve models through APIs
- Set up guardrails and response evaluation
Perks/Benefits
Skills/Tech-stack
API Development | Airflow | CI/CD | Classification | Clustering | Data Pipelines | Deep learning | Embeddings | Experiment tracking | Feature Engineering | Feature Stores | Generative AI | Go | Java | Kafka | Language Models | Language Processing | Large Language Models | MLOps | Machine Learning | Model Evaluation | Model Monitoring | Model versioning | Natural Language | Natural Language Processing | Observability | Prompt engineering | PyTorch | Python | Ranking | Recommendation Systems | Regression | Retrieval-Augmented Generation | Semantic Search | Spark | Streaming Data | Streaming data pipelines | TensorFlow | Testing | Vector Databases
Education
N/A
Roles
AI | AI Engineer | Engineer | Learning Engineer | Machine Learning Engineer
Regions
Countries
States
Cities
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