AI Engineer - Private Assets
Tasks
- Advance AI applications in financial analytics
- Apply LLM computer vision and deep learning
- Architect end-to-end ML pipelines
- Automate tasks using AI agents
- Collaborate with product teams and domain experts
- Design and implement enterprise scale AI architectures
- Develop NLP systems for metric extraction and validation
- Drive technical excellence through code reviews and design documentation
- Implement MLOps for model deployment monitoring and improvement
- Provide AI ML technical guidance and mentorship
Perks/Benefits
- Career development
- Collaborative workspaces
- Employee resource groups
- Flexible working arrangements
- Inclusion initiatives
- Learning platforms
Skills/Tech-stack
A/B | A/B Testing | Apache Beam | Apache Spark | Automated retraining | B testing | Computer Vision | Deep learning | Distributed Computing | Flink | Kafka | LLMs | Language Processing | MLOps | Model versioning | NLP | Natural Language | Natural Language Processing | PyTorch | Python | Ray | Real Time | Real-time Streaming | Series analysis | TensorFlow | Time Series | Time Series Analysis
Education
N/A
Roles
AI | AI Engineer | Engineer | Principal | Principal AI Engineer
Regions
Countries
States
Cities
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