Software Engineering & Development, VP
Tasks
- Deploy models to production
- Develop LLM and NLP features
- Develop computer vision and predictive machine learning
- Ensure performance reliability privacy compliance
- Establish MLOps best practices
- Evaluate models using an evaluation strategy
- Identify and mitigate data drift and data leakage risks
- Implement AI governance
- Lead end to end AI solution design and delivery
- Mentor AI engineers and applied scientists
- Monitor models and set up alerting
- Optimize latency and cost for AI workloads
- Review AI designs for robustness correctness security
- Run red teaming and adversarial testing
- Scale AI engineering teams
- Translate business problems into AI solution approaches
Perks/Benefits
- N/A
Skills/Tech-stack
AI Governance | APIs | AWS | Adversarial Testing | Automated Evaluation | Azure | C plus plus | CI/CD | Cloud platform | Computer Vision | Data Versioning | Deep learning | Distributed Systems | Feature management | Go | Google Cloud | Google Cloud Platform | Incident Response | Java | Language Models | Language Processing | Large Language Models | Low Latency | Low Latency Inference | MLOps | Machine Learning | Model Monitoring | Natural Language | Natural Language Processing | Observability | Prompt engineering | Python | Red Teaming | Retrieval-Augmented Generation
Education
Bachelor of Engineering | Bachelor of Science | Master of Science | PhD
Roles
AI | AI Developer | AI Engineer | Developer | Engineer | Gen AI Developer | Software Engineer
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