Mid-level AI Engineer, MLOps, AWS

This is a fully remote position, open to applicants in Brazil.

📋 Description

• Transform Machine Learning and Generative AI models into stable production services by productizing experiments.

• Construct and uphold MLOps pipelines for tasks involving training, versioning, deployment, and reprocessing.

• Implement scalable deployments that effectively balance performance, availability, and cost considerations.

• Create and train Machine Learning models to address various business challenges.

• Develop Generative AI and LLM solutions, incorporating them into products and internal workflows.

• Oversee production models by monitoring quality, degradation, and any unexpected behaviors.

• Enforce security protocols, access control measures, and safeguard sensitive data.

• Assess results and suggest enhancements based on both technical and business metrics.

• Work collaboratively with data, engineering, and business teams to identify and prioritize use cases.

⛳️ Requirements

• Proven experience in productizing AI and Machine Learning solutions, transitioning models from experimental phases to production.

• Technical independence in constructing and maintaining comprehensive end-to-end MLOps pipelines.

• Familiarity with scalable model deployment and the continuous monitoring of production environments.

• Practical experience with AWS AI and Machine Learning services, including SageMaker and Bedrock.

• Proficient in Python as applied to AI and Machine Learning initiatives.

• Understanding of SQL and data manipulation techniques for preparing datasets.

• Knowledge of security practices relevant to AI solutions and the management of sensitive information.

• Experience in developing and training proprietary Machine Learning models using tools such as scikit-learn, PyTorch, or TensorFlow.

• Background in integrating third-party LLMs through API methods.

• Familiarity with LangChain, LangGraph, LlamaIndex, or comparable technologies.

• Experience with RAG and vector databases.

• Proficient in using containers and orchestration tools, including Docker and Kubernetes.

• AWS certifications related to Machine Learning, AI, or solutions architecture.

• Prior consulting experience or experience servicing multiple clients.

• Characteristics such as autonomy, critical thinking, effective communication, thorough evaluation of results, technical curiosity, discipline, and collaboration.

• No specific educational requirements are mentioned in the job listing.

🏝️ Benefits

• Continuous training and development opportunities.

• The company is committed to investing in its workforce.

• The position is also available to candidates with disabilities.