Rockstar 3
Senior AI Engineer
United States · Senior
Sponsorship not specifiedDetected 63 days ago
PythonVector DatabasesDockerKubernetesCI/CDMachine LearningDeep LearningTensorFlowPyTorchscikit-learnData ScienceNLPLLMsRAGLangGraphAI OrchestrationResearchMentoring
About the role
- The ideal candidate combines strong machine learning expertise with practical production engineering experience.
- Fine-tune, adapt, and evaluate LLMs for domain-specific use cases using prompt engineering, supervised fine-tuning, LoRA / QLoRA, or related methods.
Responsibilities
- This person will own complex technical work from concept through deployment, mentor other engineers, and help define best practices for building reliable, observable, and secure AI systems.
- Essential Responsibilities Design, build, and deploy production GenAI systems, including LLM applications, agentic workflows, RAG pipelines, and AI-powered search capabilities.
- Implement observability for AI systems, including tracing, logging, performance monitoring, drift detection, and output-quality review.
- Partner with product managers, data engineers, backend engineers, analysts, and business stakeholders to define AI capabilities and technical tradeoffs.
Requirements
- 2+ years of experience building or shipping production GenAI, LLM, or AI-powered systems.
- Hands-on experience with PyTorch, TensorFlow, Hugging Face Transformers, scikit-learn, or similar ML frameworks.
- Experience with LLM applications, RAG systems, embeddings, vector databases, prompt engineering, and model evaluation.
- Experience deploying AI / ML services using Docker, Kubernetes, CI/CD workflows, APIs, and cloud-native infrastructure.
- Ability to communicate complex AI concepts clearly to technical and non-technical stakeholders.
Nice to have
- Experience with agent frameworks such as LangGraph, AutoGen, CrewAI, or similar tools.
- Experience with model-serving platforms such as vLLM, BentoML, Triton, Ray Serve, or similar systems.
- Familiarity with ML observability, experiment tracking, model monitoring, and prompt/version management tools.
- Experience with graph-based retrieval, knowledge graphs, multimodal models, large-scale data processing, or security-focused data products.
- Experience with infrastructure-as-code, workflow orchestration, model routing, caching, batching, or quantization.
- Special Skills or Experience Required Proven experience building and deploying production GenAI systems, including LLM applications, agentic workflows, and RAG pipelines.
- Advanced Python and ML framework experience, including PyTorch, TensorFlow, Hugging Face Transformers, or similar tools.
- Experience with LLM fine-tuning, prompt engineering, embeddings, vector databases, semantic search, and model evaluation.
Skills
- Architect scalable AI services using modern ML frameworks, model-serving tools, APIs, Docker, Kubernetes, and CI/CD pipelines.
Benefits
- Machine Learning Engineer to design, build, deploy, and maintain production-grade AI systems across their data intelligence platform.
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This listing is sourced directly from Rockstar 3's careers page and normalized into a canonical job model.