Senior AI Engineer - Private Assets
Tasks
- Apply LLMs computer vision deep learning
- Architect end-to-end machine learning pipelines
- Automate tasks using AI agents
- Collaborate with product teams
- Conduct code reviews
- Continuously improve models
- Create design documentation
- Design enterprise AI architectures
- Develop NLP systems
- Extract metrics from documents
- Implement MLOps for model deployment
- Implement enterprise AI systems
- Monitor models in production
- Provide AI ML mentorship
- Share AI/ML knowledge
- Translate requirements into scalable solutions
Perks/Benefits
- Collaborative workspaces
- Employee Career Development
- Employee resource groups
- Flexible working arrangements
- Learning platform access
Skills/Tech-stack
A/B | A/B Testing | Apache Beam | Apache Flink | Apache Spark | Automated retraining | B testing | Computer Vision | Deep learning | Distributed Computing | Kafka | Language Models | Language Processing | Large Language Models | MLOps | Machine Learning | Machine Learning Pipelines | Model versioning | Natural Language | Natural Language Processing | PyTorch | Ray | Series analysis | TensorFlow | Time Series | Time Series Analysis
Education
N/A
Roles
AI Engineer | Engineer | Principal | Principal AI Engineer | Senior AI Engineer
Regions
Countries
States
Cities
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