AI Engineer - Private Assets
Tasks
- Apply Computer Vision
- Apply LLMs
- Architect end-to-end machine learning pipelines
- Automate tasks using AI agents
- Collaborate with product teams and domain experts
- Conduct code reviews and design documentation
- Design and implement enterprise scale AI architectures
- Develop NLP systems for document extraction
- Implement Deep Learning solutions
- Implement MLOps for model deployment monitoring and improvement
- Provide AI ML mentorship and technical guidance
Perks/Benefits
- Annual bonus eligibility
- Collaborative workspaces
- Employee learning opportunities
- Flexible working arrangements
- Learning platform access
Skills/Tech-stack
A/B | A/B Testing | Apache Beam | Apache Spark | Automated Retraining Pipelines | Automated retraining | B testing | Computer Vision | Deep learning | Flink | Kafka | Language Models | Language Processing | Large Language Models | MLOps | Model versioning | NLP | Natural Language | Natural Language Processing | PyTorch | Python | Ray | Retraining Pipelines | Series analysis | Streaming Architecture | 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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