N
AI Engineer
Sin especificarTiempo completoAI EngineeringCybersecurity
Develop and deploy practical AI solutions, including agents, retrieval-augmented generation systems, knowledge systems, and reusable AI services. Lead initiatives from research and proof of concept through production while collaborating with development, product, and business teams.
Responsabilidades
- Research and evaluate emerging AI technologies and identify valuable use cases.
- Design and develop RAG systems, knowledge systems, AI agents, and multi-agent workflows.
- Lead AI solutions from research and proof of concept through design, development, and production.
- Integrate AI models, agents, data, and reusable AI services into existing systems.
- Evaluate and benchmark solutions across quality, accuracy, latency, throughput, and cost.
- Advance the organization’s internal AI ecosystem and address complex technical and business challenges.
Requisitos
- At least 3 years of experience in software engineering, machine learning engineering, applied AI, or a related technical role.
- Strong Python skills and experience building production-grade software, APIs, and microservices.
- Hands-on experience developing AI-powered applications and taking them from proof of concept to production.
- Strong understanding of large language models and transformer architectures.
- Experience with retrieval-augmented generation, embeddings, and vector databases.
- Experience developing AI agents, tool-using workflows, MCP integrations, or similar technologies.
- Experience evaluating and benchmarking AI models and solutions.
- Familiarity with model-serving technologies such as vLLM, LiteLLM, SGLang, TGI, or Triton.
- Working knowledge of Docker, Kubernetes, Helm, Linux, Git, CI/CD, and GitOps.
Se valora
- Experience with PyTorch, Hugging Face Transformers, or similar frameworks.
- Experience with fine-tuning methods such as LoRA, QLoRA, supervised fine-tuning, preference optimization, or distillation.
- Experience with GraphRAG, knowledge graphs, code graphs, or other graph-based AI systems.
- Experience optimizing inference through quantization, batching, caching, parallelism, or GPU-aware deployment.
- Experience with multimodal models, synthetic data generation, or AI model evaluation.
- Experience delivering AI solutions in security-sensitive, regulated, on-premises, or disconnected environments.
- Bachelor’s degree in Computer Science or equivalent experience.