Senior Associate/Manager - Applied AI Engineer, Technology Consulting
Tasks
- Build inference stacks
- Build model guardrails and evals
- Conduct transformer internals analysis
- Configure multi GPU inference
- Contribute to distributed training
- Create monitoring and observability for AI systems
- Deploy and operate open source models
- Design model evaluation infrastructure
- Develop fine-tuning pipelines
- Establish CI/CD pipelines
- Fine-tune and distill models
- Implement infrastructure-as-code
- Implement quantization for inference
- Implement retrieval infrastructure
- Manage IAM and VPC networking
- Manage context and cost for model usage
- Mentor and lead a small team
- Own production AI system architecture
- Provision cloud GPU orchestration
- Run model serving with vLLM or TGI
- Select frontier vs open source models
- Set up autoscaling for inference workloads
- Track research and assess production readiness
Perks/Benefits
- N/A
Skills/Tech-stack
ALiBi | AWS | AWS CDK | Attention Mechanisms | Autoscaling | Azure | CI/CD | CUDA | DPO | DeepSpeed | Docker | Evaluation Frameworks | FSDP | GCP | GPU Computing | Grafana | Hugging Face | IAM | KV cache | Kubernetes | LoRA | Model Monitoring | ORPO | OpenTelemetry | Prometheus | Pulumi | PyTorch | Python | QLoRA | Quantization | ROPE | Retrieval-Augmented Generation | SGLang | Structured outputs | TensorRT-LLM | Terraform | Text Generation | Text generation inference | Tokenization | Tool use | Transformers | VLLM | VPC
Education
N/A
Roles
AI | AI Engineer | Applied AI Engineer | Engineer | Learning Engineer | Machine Learning Engineer
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