About Plexe

Open-source agents to build predictive ML models from a prompt

Tech description:

Plexe uses a self-correcting team of ML engineering agents to research, experiment, evaluate, refine, and deploy the best performing model over an API endpoint. The agents connect to data sources, discover relevant fields, and autonomously build and deploy ML models.

Job description:

## The Role We're seeking a Forward Deployed Engineer to work directly with customers, helping them integrate Plexe and build complete ML pipelines using our platform. You'll be part technical consultant, part solutions architect, and part implementation partner—traveling to customer sites, understanding their unique challenges, and ensuring they achieve success with our ML Engineering platform. If you love solving complex problems in real-world environments and thrive on customer interaction, this role is for you. ## What You'll Do * **Customer Engagement:** Visit customer sites to understand their ML workflows, pain points, and business objectives. You'll be the technical face of Plexe, building relationships and trust with engineering teams. * **Integration & Implementation:** Help customers integrate Plexe into their existing infrastructure and build end-to-end ML pipelines using our multi-agent platform. You'll work hands-on with their data, models, and systems. * **Solution Architecture:** Design custom ML pipeline solutions that leverage Plexe's capabilities while fitting seamlessly into customer environments. Each implementation will be unique to their specific needs. * **Technical Support & Training:** Provide ongoing technical support, conduct training sessions, and create documentation to ensure customers can effectively use and maintain their Plexe implementations. * **Product Feedback Loop:** Capture customer requirements, pain points, and feature requests to inform our product roadmap. You'll be the voice of the customer within our engineering team. ## What We Need We're looking for someone who combines strong technical skills with excellent customer-facing abilities: * **3+ years** building and deploying ML systems in production environments * **Strong Python** and experience with ML frameworks (PyTorch, TensorFlow, scikit-learn) * Experience with **LLM deployment** and agentic systems * **Customer-facing experience** with ability to present technical concepts to diverse audiences * **Problem-solving mindset** with ability to debug and troubleshoot in unfamiliar environments **Nice-to-Have:** * Background in **consulting** or customer success roles * Experience with **data engineering** and pipeline orchestration tools * Understanding of **enterprise security** and compliance requirements ## Why This Role? This isn't your typical engineering position - you'll have direct impact on customer success while working with cutting-edge AI technology. You'll see firsthand how your work transforms businesses, build deep relationships with customers, and help shape the future of ML pipeline development. **Travel:** This role involves 30-50% travel to customer sites, with opportunities to work with companies across various industries and scales. Ready to be the bridge between innovative AI technology and real-world customer success? Let's talk.

Plexe remote jobs

Founding Engineer (Full-Stack)

Forward Deployed Engineer