Staff Applied Machine Learning Engineer
Hybrid in Austin, TX
Full Time
C2C NOT AVAILABLE FOR THIS OPPORTUNITY
IQ Clarity is looking for a Staff Applied Machine Learning Engineer who will play a key role in transforming machine learning capabilities into production-ready product features.
This is a highly hands-on individual contributor role with significant ownership. You will be responsible for ensuring ML-driven features function end-to-end in real-world environments—from integrating models and retrieval systems to orchestrating agent workflows and ensuring they meet user expectations.
You will collaborate closely with ML researchers and engineers who focus on model development, while taking responsibility for integrating, validating, and scaling those components within a complete system.
This role requires someone who can move სწრაფly to prototype and validate ideas, while also applying strong engineering discipline to build reliable, maintainable, and testable systems. A key focus will be continuously improving code quality without slowing down iteration.
Key Responsibilities
- Own the delivery of ML-powered features from concept through production, ensuring they perform effectively in real-world use
- Integrate models, retrieval systems, and agent workflows into cohesive, functioning systems
- Lead implementation efforts, coordinating across engineering and ML teams to ship features
- Build and maintain evaluation frameworks, including datasets, scoring methods, and regression testing
- Design and refine prompts and agent behaviors to ensure predictable and accurate system outputs
- Improve observability, debugging, and testing practices for ML systems
- Enhance the reliability, structure, and maintainability of the ML codebase
- Work primarily in Python, with contributions to Go and other languages as needed
- Develop and optimize pipelines, retrieval systems, and model behaviors
- Orchestrate workflows across APIs, external services, and multiple data sources
- Balance rapid experimentation with long-term system quality
- Collaborate with stakeholders to ensure solutions align with real-world usage
Qualifications
- Strong software engineering background with experience building and owning production systems end-to-end
- High proficiency in Python and experience writing clean, maintainable code
- Proven experience delivering complex features in production, ideally involving ML/AI systems
- Ability to take ownership of ambiguous problems and drive them to practical solutions
- Experience with LLMs, retrieval-augmented generation (RAG), or agent-based systems
- Experience integrating APIs, services, and data sources into unified products
- Familiarity with ML evaluation systems and quality measurement approaches
- Strong debugging skills, including handling edge cases and production issues
- Experience with observability and monitoring in ML or backend systems
- Familiarity with pipelines, ranking systems, fine-tuning, or prompt engineering
- Comfortable working in fast-paced, high-ownership environments
- Exposure to Go or multi-language backend systems is a plus
- Experience working with customer-facing systems and incorporating user feedback
- Familiarity with full-stack or frontend development is a plus
- Experience with MLOps, data pipelines, or production ML infrastructure
- Exposure to modern open-source models is beneficial
What We’re Looking For
- Strong ownership mindset with a focus on delivering working systems
- Solid product judgment and understanding of user impact
- Bias toward action and rapid iteration
- Comfort operating in ambiguous, evolving environments
- Systems thinking with attention to correctness and edge cases
- Curiosity about real-world system behavior and user interaction
- Collaborative, low-ego approach with a focus on team success
IQ Clarity is an equal opportunity employer
