Machine Learning / AI Engineer Senior - Databricks - Eng

Accountabilities • Lead end-to-end AI and Machine Learning implementations, acting as a primary technical consultant and translating client business needs into effective technical solutions.

• Communicate technical findings, proposals, implementation plans, and project progress clearly to technical and non-technical stakeholders.

• Design, develop, deploy, and maintain production-grade AI/ML pipelines, applying CI/CD principles and advanced MLOps/AIOps practices to improve reliability, scalability, and performance.

• Build and optimize Generative AI and Agentic AI applications, including multi-agent orchestration, agent evaluation, and Retrieval-Augmented Generation (RAG) systems for production environments.

• Architect end-to-end solutions incorporating traditional Machine Learning and Generative AI according to customer requirements.

• Manage the infrastructure supporting production deployments, leveraging Docker, pipeline orchestration tools, and lakehouse platforms such as Databricks.

• Apply distributed computing technologies, including Apache Spark, to support scalable Machine Learning workloads and high-performance data processing.

• Contribute to the strategic development of the AI Forward Deployed Engineering (FDE) practice through technical assignments, collaboration, and knowledge transfer.

• Document and report client engagements, project deliverables, and training activities through designated partner platforms.

Requirements

• At least 4 years of hands-on professional experience developing, deploying, and managing Generative AI, Agentic AI, or Machine Learning systems, including a proven ability to productionize and maintain models in live environments.

• At least 3 years of experience in client-facing consulting or solutions architecture , with a focus on technical implementation and delivery.

• Strong Python programming skills for data-intensive, scalable AI/ML applications.

• Expertise in MLOps lifecycle management, including model versioning, testing, monitoring, continuous integration, and automated deployment.

• Practical experience managing infrastructure for AI/ML workloads, including Docker containerization and data pipeline orchestration.

• Familiarity with distributed computing frameworks such as Apache Spark and lakehouse technologies such as Databricks.

• Hands-on experience developing production-ready Generative AI and Agentic AI solutions, including multi-agent systems, agent evaluation, and RAG architectures.

• Excellent written and verbal communication skills, with the ability to collaborate effectively with clients, stakeholders, and multidisciplinary teams.

• Strong problem-solving skills, technical ownership, adaptability, and a commitment to continuous learning in the evolving AI/ML landscape.

• A collaborative mindset, positive attitude, and willingness to contribute to shared technical knowledge and team development.

Benefits

• Remote-first work environment , offering flexibility to work remotely. Eligibility to work remotely from Brazil should be confirmed during the hiring process, as the original listing identifies the role as remote within Latin America.

• Full coverage for professional certifications in AWS, dbt, Google Cloud, Azure, and Databricks.

• In-company English language lessons.

• Birthday leave and an additional vacation week through the company's annual team break.

• Employee referral bonuses.

• Monthly credits for a benefits marketplace, providing access to a range of employee perks.

• An annual team trip designed to encourage connection and collaboration.

• Monthly childcare reimbursement to support employees and their families.

• Salary, healthcare coverage, and other compensation details are not specified in the provided listing and should be confirmed during the recruitment process.

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