Service Delivery Center, AI & Data, Machine Learning Engineer (MLE) - Senior
Tasks
- Architect and deploy production grade AI agents
- Build MLOps pipelines for continuous model improvement
- Build multi agent systems for financial workflows
- Connect AI agents to enterprise knowledge bases and real time data
- Contribute to AI research initiatives and patent applications
- Deploy AI agents with low latency
- Design agentic reasoning within regulatory boundaries
- Fine tune LLMs for financial domain tasks
- Implement retrieval augmented generation systems
- Monitor and observe AI agent systems
- Optimize inference costs for performance SLAs
- Present solutions to executives
- Prototype AI applications for trading compliance and fraud detection
- Run A B testing for model evaluation
- Translate regulations into AI agent behaviors
Perks/Benefits
- N/A
Skills/Tech-stack
A/B | A/B Testing | AWS SageMaker | Autogen | Azure OpenAI | Azure OpenAI Service | B testing | Chroma | Claude | Context learning | Continuous Deployment | CrewAI | Drift Detection | Fine Tuning | Flink | GANs | GPT-4 | Google Vertex | Google Vertex AI | In-context Learning | Kafka | Langchain | Language Models | Large Language Models | Llama | LoRA | MLOps | Model Fine-tuning | Model versioning | OpenAI Service | PEFT | Pinecone | Prompt engineering | Python | QLoRA | Transformers | Vector Databases | Vertex AI | Weaviate
Education
N/A
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