Machine Learning Engineer

• Build and Integrate AI Solutions
• Design and implement AI-driven data pipelines and systems that integrate seamlessly with existing client infrastructure
• Develop production-ready ML solutions using modern frameworks and cloud platforms
• Architect scalable AI systems that prioritize reliability, maintainability, and performance
• Collaborate with software engineering teams to embed AI capabilities into production applications
• Implement MLOps best practices including model versioning, monitoring, and continuous deployment
• Create fast, compelling prototypes that demonstrate AI value to clients and stakeholders
• Translate client problems into concrete AI/ML solutions with quick turnaround times
• Experiment with emerging AI technologies and agentic tools (Claude Code, GitHub Copilot, AWS Q, etc.) to accelerate development
• Build proof-of-concept applications that showcase the art of the possible
• Participate in client meetings and calls, translating technical concepts into business value
• Work closely with project technical leads across multiple client engagements
• Communicate AI capabilities, limitations, and recommendations to both technical and non-technical audiences
• Gather requirements and provide technical consultation on AI feasibility and implementation approaches
• Fine-tune or train models when existing solutions don't meet client needs
• Evaluate and select appropriate pre-trained models and AI services
• Conduct model performance analysis and optimization

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