Machine Learning Solutions Engineer

Lightning AI is the company reimagining the way AI is built. After creating and releasing PyTorch Lightning in 2019, Lightning AI was launched to reshape the development of artificial intelligence products for commercial and academic use.

We are on a mission to simplify AI development, making it accessible to everyone—from solo researchers to large enterprises. By removing the complexity of building and deploying AI tools, we empower innovators to focus on solving real-world problems. Our platform is built to scale with the latest AI advancements while staying intuitive and adaptable, so you can bring your ideas to life.

We have offices in New York City, San Francisco, and London and are backed by investors such as Coatue, Index Ventures, Bain Capital Ventures, and First minute.

Move Fast
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We act with speed and precision, breaking down big challenges into achievable steps.

Focus
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We complete one goal at a time with care, collaborating as a team to deliver features with precision.

Balance
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Sustained performance comes from rest and recovery. We ensure a healthy work-life balance to keep you at your best.

Craftsmanship
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Innovation through excellence. Every detail matters, and we take pride in mastering our craft.

Minimal
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Simplicity drives our innovation. We eliminate complexity through discipline and focus on what truly matters.

As a customer facing Machine Learning Solutions Engineer, you will work closely with our go-to-market teams as the technical subject matter expert. You will be responsible for demos, proof-of-concepts, and post sales technical support. As a Machine Learning Solutions Engineer, you will also have the opportunity to work with our product and engineering team on product features. This is a collaborative role that works with engineering, design, product and sales.

You will be joining the Sales team and report to our MLSE Team Lead. This is a hybrid role based in our New York City office with in-office requirements of 3 days per week. The salary range for this role is $120,000 - $175,000.

• Write readable/testable/efficient code in Python
• Partner with customers to understand their machine learning (ML) workflows, challenges, and goals, providing technical expertise to help them achieve success with Lightning AI’s platform.
• Scope and deliver proof-of-concepts that align customer goals with the strengths of our platform.
• Work with customers to build and optimize ML models and pipelines for diverse use cases, working hands‑on with customer data and applications.
• Design and deliver technical workshops, demos, and training sessions tailored to customer needs.
• Collaborate closely with internal teams—including product, engineering, and sales—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.
• Troubleshoot and resolve 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.

• 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, ML Consultant) is highly desirable.
• Understanding of machine learning concepts, tools, and best practices.
• Proficiency in Python and experience with ML frameworks such as PyTorch or Tensor Flow. Familiarity with Lightning AI’s open source portfolio is a plus.
• Proven ability to debug, optimize, and implement ML models and pipelines in production environments.
• 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…