Senior Machine Learning Engineer

What you'll do

• Design and manage CI/CD pipelines for model versioning, automated deployment, and release management.
• Build and monitor observability infrastructure for model performance, data quality, latency, and cost.
• Develop production-scale AI systems including multi-step agentic workflows and multi-agent orchestration platforms.
• Implement Responsible AI frameworks featuring hallucination detection, safety guardrails, and evaluation systems.
• Establish evaluation frameworks for Large Language Models to measure quality, task success, and safety compliance.
• Champion LLMOps and MLOps best practices using infrastructure-as-code and automated testing.
• Lead architectural decisions for AI development, quality assurance, and production deployment.
• Research and integrate emerging AI technologies and frameworks to advance the platform's capabilities.

What we're looking for

• Bachelor's degree in Computer Science, Machine Learning, Mathematical Sciences, Information Systems, Software, Electrical or Electronics Engineering, or a comparable field.
• Master's degree or Ph.D. in a relevant technical field (preferred).
• 5+ years of experience designing, building, and deploying AI/ML solutions at scale.
• 1–2 years of production experience in Generative AI technologies.
• Expert-level programming proficiency in Python and AI/ML development ecosystems.
• Comprehensive MLOps/LLMOps experience including CI/CD pipelines, model versioning, and production lifecycle management.
• Production deployment experience on major cloud platforms such as AWS, Azure, or GCP.
• Experience with container orchestration, infrastructure-as-code, vector databases, and embedding technologies (preferred).