Senior ML Ops Engineer
USD 95K-171K Senior-level Full Time
Tasks
- Apply NLP and RAG research to production systems
- Automate machine learning workflows
- Build evaluation pipelines and metrics
- Build retrieval pipelines with search vector and graph databases
- Design and implement RAG systems components
- Develop CI/CD for ML
- Implement MLOps platforms solutions
- Interface with operations for production deployments
- Maintain model registries and artifact stores
- Manage prompt libraries and LLM guardrails
- Optimize infrastructure costs through monitoring and scaling
- Run A B testing for model quality
- Scale machine learning pipelines
- Translate business problems into data science solutions
Perks/Benefits
- N/A
Skills/Tech-stack
A/B | A/B Testing | AWS | Amazon SageMaker | Azure | Azure Machine Learning | B testing | Bedrock | CI/CD | Databricks | Elasticsearch | Elasticsearch OpenSearch | Elasticsearch OpenSearch Solr | Graph Database | Information Retrieval | Java | Language Processing | MAP | MLOps | MLflow | MRR | Machine Learning | NDCG | Natural Language | Natural Language Processing | Neo4j | OpenAI | OpenSearch | PySpark | PyTorch | Python | RAG | Scala | Solr | Spark | TensorFlow | Vector Database
Education
N/A
Regions
Countries
States
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