AI/ML Engineer

Experience Level: 2-4 and 4-6 Years

Company Description

ZenoQuad Technologies is a collective of passionate visionaries transforming ideas into groundbreaking software solutions. Our team wields code as a canvas to create innovative products that propel businesses forward. We aim to push technological boundaries to deliver top-notch software. Join us in our mission to bring visionary ideas to life.

Role Description

This is a full-time remote role for an AI/ML Engineer. The AI/ML Engineer will be responsible for developing and implementing machine learning models, performing data analysis, and collaborating with cross-functional teams to build AI solutions.

• Experience in Machine Learning and LLM Evaluation metrics – RAGAS/ DeepEval Framework and Langfuse platform for observability and evaluation

• Experience in developing and implementing the framework for metrics evaluation and monitoring the ML/Gen AI-based solutions

• Hands-on experience with Docker and Kubernetes (preferred), along with cloud services like AWS or equivalent platforms

• Strong foundation in programming, including data structures, algorithms, and distributed systems

• Experience working in Agile/Sprint environments and debugging complex systems or applications

• Knowledge of ISO42001 framework, Responsible AI standards, and AI governance

• Design, develop, and deploy AI/ML-driven applications and services.

• Build and maintain scalable, secure, and resilient full-stack applications.

• Integrate observability tools (e.g., Langfuse or similar) to monitor, trace, and improve ML-powered systems.

• Write clean, efficient, and maintainable code in Python or Java.

• Leverage tools like Llama Parser to build and optimize ML pipelines and applications.

• Contribute to architectural decisions and best practices for ML systems in production.

• Troubleshoot performance issues and optimize ML workflows for efficiency.

Required Qualifications:

• 2–6 years of professional experience as a Software Engineer or AI/ML Engineer.

• Strong programming skills in Python or Java.

• Solid understanding of full-stack development (backend, APIs, databases).

• Hands-on experience with large language models (LLMs) and related frameworks.

• Knowledge of observability and monitoring tools like Langfuse.

• Hands-on experience with Llama Parser for ML/LLM-powered applications.

• Experience with cloud platforms like AWS.

• Proven ability to design, build, and scale production-ready applications.

• Strong problem-solving and debugging skills.