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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