Mid-level AI Engineer, MLOps, AWS
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Job Description
Engenheiro de IA levando Machine Learning e IA Generativa à produção na Leega. Construindo pipelines MLOps escaláveis, seguros e monitorados no ecossistema AWS.
Responsibilities:
- Productize Machine Learning and Generative AI models, turning experiments into stable production services
- Build and maintain MLOps pipelines for training, versioning, deployment, and reprocessing
- Implement scalable deployments, balancing performance, availability, and cost
- Develop and train Machine Learning models for business problems
- Build Generative AI and LLM solutions, integrating them into products and internal processes
- Monitor production models, tracking quality, degradation, and unexpected behavior
- Apply security practices, access control, and protection of sensitive data
- Evaluate results and propose improvements based on technical and business metrics
- Collaborate with data, engineering, and business teams to define and prioritize use cases
Requirements:
- Experience productizing AI and Machine Learning solutions, taking models from experiments to production
- Technical autonomy to build and maintain end-to-end MLOps pipelines
- Experience with scalable model deployment and continuous production monitoring
- Hands-on experience with AWS AI and Machine Learning services: SageMaker and Bedrock
- Proficiency in Python applied to AI and Machine Learning solutions
- Knowledge of SQL and data manipulation for dataset preparation
- Knowledge of security practices applied to AI solutions and handling sensitive data
- Experience developing and training in-house Machine Learning models using scikit-learn, PyTorch, or TensorFlow
- Experience integrating third-party LLMs via API
- Experience with LangChain, LangGraph, LlamaIndex, or similar
- Experience with RAG and vector databases
- Experience with containers and orchestration, such as Docker and Kubernetes
- AWS certifications focused on Machine Learning, AI, or solutions architecture
- Previous consulting experience or servicing multiple clients
- Autonomy, critical thinking, clear communication, rigor in evaluating results, technical curiosity, discipline, and collaboration
- No explicit educational requirement stated in the listing
Benefits:
- Ongoing training and development
- Company invests in its employees
- Position also open to candidates with disabilities
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