Senior MLOps Engineer

Role Overview

• Lead the design and development of AI/ML, MLOps and Agentic AI solutions;
• Develop and optimize machine learning models and pipelines;
• Implement LLM-based pipelines;
• Deploy models and vector memory systems;
• Collaborate with Data Science, Software Engineering and DevOps teams;
• Gather requirements from clients and identify technical opportunities;
• Ensure clear communication about status and deliveries;
• Identify process improvements and automation opportunities;
• Maintain production AI and MLOps environments;
• Other routine tasks within the area.

Requirements

• Strong experience focused on Artificial Intelligence, Machine Learning and MLOps;
• Experience working as an MLOps Engineer or MLOps Lead;
• Advanced proficiency in Python development;
• Experience with Java for integration and development of enterprise solutions;
• Hands-on experience with TensorFlow, PyTorch and TFX for developing and optimizing Machine Learning models;
• Experience with Flask and TorchServe for deploying and managing models in production;
• Solid experience with Google Cloud Platform (GCP), including Vertex AI and Kubeflow;
• Experience creating, maintaining and optimizing MLOps pipelines in cloud environments;
• Knowledge of model deployment, real-time inference and batch processing;
• Experience in Model Engineering, including training, validation and fine-tuning of models;
• Practical experience with Generative AI, NLP and RAG (Retrieval-Augmented Generation) architectures;
• Knowledge of Agentic AI frameworks and tools such as Google ADK, LangChain, LangGraph, CrewAI, Semantic Kernel, AutoGen and OpenAI Agent SDK;
• Experience integrating tools like Gemini Tools and developing custom MCP Tools;
• Experience with relational and non-relational databases such as Oracle, DB2, BigQuery, Cassandra and PostgreSQL;
• Experience with GitHub and version control in collaborative environments;
• Required: Bachelor’s degree completed;
• Preferred: Knowledge of GPU Programming;
• Experience with GPU Profiling and GPU Optimization;
• Knowledge of TensorRT;
• Experience with AutoML;
• Experience with advanced architectures for Generative AI and Agentic AI;
• Experience in large enterprise environments focused on scalability of AI/ML solutions.

Tech Stack

• BigQuery
• Cassandra
• Cloud
• Flask
• Google Cloud Platform
• Java
• Oracle
• Postgres
• Python
• PyTorch
• Tensorflow

Benefits

• Medical coverage for employees and dependents with nationwide coverage via Bradesco or Unimed;
• Dental coverage with nationwide coverage;
• Meal voucher or food voucher (employee's choice);
• Childcare allowance;
• Life insurance for employees and dependents;
• Gympass for employees and dependents;
• EAP (Employee Assistance Program) with services: Financial Assistance, Legal Assistance, Social Assistance, Psychological Assistance (24/7);
• Discounts and special rates with universities (Mackenzie, SENAC, FIA, FIAP and BBS Business School) and language schools (CNA, Cultura Inglesa, Wizard, CCAA, Indeed);
• Discounts on fee packages and special rates with Itaú and Bradesco banks;
• Option for payroll-deductible loans, with repayments directly deducted from the employee's salary;
• Reimbursement program for certain external certifications;
• Training: The company provides an online and in-person training and development platform covering soft skills, technologies and domains with more than 15,000 topics;
• Longevity awards: The company rewards employees for their commitment and loyalty during their tenure (3, 5 and 10 years and every 5 years thereafter);
• Employee referral bonus – a bonus for each successful hire;
• Fit4life – Program to encourage physical exercise among employees, with scheduled online functional training;
• International experience: Depending on your skills and business needs, you may apply for positions abroad (within and outside Latin America);
• And others.