Senior, Data Scientist (Machine Learning Engineer)
USD 117K-234K (estimate) Senior-level Full Time
Tasks
- Apply GenAI NLP and computer vision for compliance detection
- Build and optimize batch and real time inference pipelines
- Create technical documentation and share knowledge
- Deploy and monitor ML models in production
- Design and deploy production ML systems
- Drive ML architecture decisions
- Establish ML engineering best practices
- Own model lifecycle from experimentation to production
- Translate business requirements into model KPIs and evaluations
Perks/Benefits
- N/A
Skills/Tech-stack
Airflow | Azure | Batch inference | CI/CD | CNN | Cloud Platforms | Computer Vision | Data Drift | Data Drift Detection | Deep learning | Distributed Computing | Docker | Drift Detection | Experiment tracking | Fine Tuning | GCP | Generative AI | Git | Helm | Huggingface | Hybrid retrieval | Inference Optimization | Inference Server | Kubeflow | Kubernetes | LLMs | Language Processing | LoRA | ML observability | MLflow | Machine Learning | Model Monitoring | Natural Language | Natural Language Processing | NoSQL Databases | NumPy | PEFT | PGVector | Pinecone | Prompt engineering | PyTorch | Python | QLoRA | RAG | Ray | Real Time | Real-time Inference | Relational databases | Scikit-learn | Spark | Torchserve | Transformers | Triton Inference | Triton Inference Server | VLLM | Vector Databases | Weaviate | Weights and Biases
Education
Regions
Countries
States
Cities
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