Machine Learning Solutions Engineer
Partners with customers to solve ML challenges using Lightning AI platform, delivers demos/workshops/POCs, architects solutions, and influences product roadmap. Requires 3-5+ years ML experience, Python/PyTorch proficiency, and customer-facing technical skills.
What You’ll Do
- Partner with customers to understand their ML workflows, challenges, and goals, providing technical expertise to help them achieve success with Lightning AI’s platform.
- Design and deliver demos, technical workshops, and training sessions
- Write readable and concise Python code for demos & templates
- Scope and lead POCs that align customer success criteria with the core differentiators of the Lightning AI platform
- Collaborate closely with internal teams—including product and engineering—to relay customer feedback, advocate for feature enhancements, and influence the product roadmap.
- Develop technical documentation and tutorials to empower customers and improve their ML workflows.
- Architect solutions for complex technical challenges faced by customers, acting as their advocate within Lightning AI.
- Stay up-to-date with the latest advancements in ML frameworks, tools, and best practices, sharing knowledge with both internal teams and customers.
What You’ll Need
- 3–5+ years of hands-on experience with machine learning, data science, or a related field. Customer-facing experience in a technical role (e.g., Solutions Engineer, Sales Engineer, ML Consultant) is highly desirable.
- Understanding of machine learning concepts, tools, and best practices.
- Experience with Python and ML frameworks such as PyTorch. Familiarity with Lightning AI’s open source portfolio is a plus.
- Proven ability to debug, optimize, and implement ML/AI models and pipelines.
- Exceptional written and verbal communication skills, with the ability to explain technical concepts to both technical and non-technical audiences.
- Experience working cross-functionally with engineering, product, and sales teams to deliver tailored solutions.
- Thrive in a dynamic, customer-driven environment, balancing multiple projects and priorities simultaneously.
- A degree in Computer Science, Data Science, or a related field, or equivalent practical experience. Advanced degrees are a plus.
Compensation
The annual base pay range for this role is $150,000 - $195,000, in addition to a variable pay component and meaningful equity.
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