MLOps Engineer

Posted Aug 13

This is a fully remote position, open to applicants in Argentina, +4 more countries.

📋 Description

• Design, implement, and sustain a cloud-native platform that supports AI and data workloads, with a focus on Databricks and AWS Bedrock.

• Construct and oversee scalable data pipelines for machine learning and analytics applications.

• Develop infrastructure-as-code using CloudFormation and AWS CDK.

• Integrate AI models and large language models into production systems, including retrieval-augmented generation architectures and model-serving workflows.

• Enhance observability through monitoring, alerting, and logging across AI platforms.

• Collaborate with AI engineers, data engineers, and platform teams to optimize model performance, reliability, and cost-effectiveness.

• Contribute to the advancement of the AI platform for new machine learning frameworks, workflows, and data types.

• Keep up-to-date with emerging tools and suggest improvements in architecture and operations.


⛳️ Requirements

• Over 7 years of professional experience in software and infrastructure engineering.

• Extensive hands-on experience in building and maintaining AI/ML infrastructure, including model deployment, lifecycle management, and serving workflows.

• Proficient experience with Databricks and MLflow, covering model registration, versioning, asset bundles, and serving.

• Strong knowledge of AWS and infrastructure-as-code, particularly AWS CDK.

• Advanced coding abilities in Python and TypeScript for developing robust APIs and backend services.

• Solid understanding of Docker containerization and practical experience with CI/CD pipelines.

• Capability to design reliable, secure, and scalable infrastructure for both real-time and batch machine learning workloads.

• Excellent communication and collaboration skills.

• Familiarity with DSPy or similar LLM orchestration frameworks.

• Experience in LLM cost monitoring, latency optimization, and usage analytics in production environments.

• Knowledge of vector databases and embedding stores such as OpenSearch for semantic search and retrieval-augmented generation architectures.

• Experience with ECS or other container orchestration tools.

• Required English proficiency level as specified in the application form.

• Legal authorization to work in the country where the position is located, as indicated in the application form.


🏝️ Benefits

• Engage in real-world AI-driven projects across various key industries.

• Collaborate with a global team spanning multiple continents and cultures.

• Enjoy an inclusive environment.

• Benefit from continuous learning opportunities.

• Work in an innovation-focused atmosphere.

• Uphold ethical AI standards.

• Be part of an equal opportunity employer.

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