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Founding Machine Learning Engineer Jobs in USA 2026

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Founding Machine Learning Engineer Jobs in USA 2026

Machine learning engineering roles continue to evolve beyond model development into full lifecycle ownership of AI systems. This Founding Machine Learning Engineer opportunity in the United States is designed for experienced AI professionals who want to help shape early-stage product direction while building production-ready systems that combine LLM-powered agents with advanced time-series modelling capabilities.

About the Role

The Founding Machine Learning Engineer will play a foundational role in designing, training, deploying, and operating machine learning systems that integrate autonomous AI agents with time-series foundation models.

This is a highly hands-on position focused on taking ideas from experimentation to production deployment. The successful candidate will work across the entire ML lifecycle while helping define how intelligent agents interact with structured, numerical, and multimodal data in emerging application environments. The role combines engineering execution, applied AI research, and product collaboration within a fast-paced startup setting.

About the Hiring Organisation

The opportunity is offered by a stealth-stage startup operating in the artificial intelligence and machine learning space. The company is focused on developing next-generation production AI systems by combining agent-based architectures with advanced forecasting and multimodal modelling approaches. As an early engineering hire, the successful candidate will help influence technical direction, platform decisions, and product development strategy.

Job Duties

  • Design, train, deploy, and maintain production machine learning systems.
  • Build and scale LLM-powered agents with reasoning, memory, tool integration, and autonomous workflow capabilities.
  • Develop evaluation frameworks to measure reliability, safety, and agent performance.
  • Apply time-series modelling techniques including forecasting, anomaly detection, and multimodal learning.
  • Manage full ML pipelines from data ingestion through deployment and monitoring.
  • Implement reproducible ML workflows and engineering best practices.
  • Maintain observability, model performance tracking, and continuous improvement processes.
  • Evaluate and adopt emerging agent frameworks and AI infrastructure technologies.
  • Collaborate with researchers, engineers, and customers to validate solutions.
  • Contribute to technical architecture and product roadmap decisions.

Job Requirements

  • Four to ten years of industry experience in Machine Learning Engineering, Applied AI, or Research Engineering.
  • Strong hands-on experience building production-grade LLM-powered agents.
  • Deep understanding of agent evaluation, reliability, and safety methodologies.
  • Experience with modern agent infrastructure and orchestration frameworks.
  • Strong software engineering practices including CI/CD, monitoring, and scalability.
  • Experience deploying end-to-end machine learning systems.
  • Ability to work effectively in fast-moving startup environments.
  • Strong communication and cross-functional collaboration skills.

Preferred Qualifications

  • Experience training custom neural networks beyond pre-trained language models.
  • Background in time-series forecasting and anomaly detection.
  • Experience with multimodal machine learning systems.
  • Published research or open-source contributions in AI or ML.
  • Experience building advanced transformer architectures.

#339966;">#339966;" href="https://www.linkedin.com/jobs/view/founding-machine-learning-engineer-32913-at-stealth-startup-4428909439/" target="_blank" rel="noopener">Click Here to Apply

Conclusion

This Founding Machine Learning Engineer position presents an opportunity to work at the intersection of autonomous agents and advanced machine learning systems within an early-stage environment. For professionals interested in production AI, time-series modelling, and shaping technical direction from the ground up, the role offers significant ownership, experimentation, and long-term growth potential.

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