VP - AI Engineering Lead
Building 300-Whippany Campus, Jefferson Park, United States
USD 150K-230K Senior-level Full Time
Tasks
- Architect AI data ingestion pipelines
- Build data pipelines
- Build low latency inference systems
- Build streaming architectures
- Clean, wrangle, transform data
- Collaborate with business stakeholders
- Deliver AI programs
- Deploy and monitor AI models
- Deploy generative AI systems
- Design generative AI systems
- Develop machine learning models
- Develop predictive models
- Ensure responsible AI governance
- Extract data from sources
- Forecast outcomes
- Implement LLM applications
- Implement retrieval-augmented generation
- Integrate tools and agents
- Lead engineering teams
- Manage MLOps lifecycle
- Manage model risk and controls
- Manage risks and strengthen controls
- Orchestrate prompts
- Perform feature engineering
- Translate business problems to AI solutions
Perks/Benefits
Skills/Tech-stack
AWS | Agentic Systems | Apache Spark | Auditability | Azure | Bias Mitigation | Docker | Explainability | Fine Tuning | Generative AI | Kafka | Kinesis | Kubernetes | Language Models | Large Language Models | Lifecycle Management | Low Latency | Low Latency Inference | MLOps | Machine Learning | Model Deployment | Model Lifecycle | Model Lifecycle Management | Model Monitoring | Model Risk Management | Model risk | Prompt orchestration) | PyTorch | Python | Real Time | Real-time Streaming | Responsible AI | Retrieval-Augmented Generation | Risk Management | Safety Guardrails | Scikit-learn | TensorFlow | Tool use
Education
N/A
Roles
AI | AI Engineering | AI Engineering Lead | Engineer | Engineering Lead | Lead | Learning Engineer | Machine Learning Engineer | VP | VP AI | VP AI Engineering Lead | VP, AI Engineering
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