Founding Machine Learning Engineer

About the role

As a Founding Machine Learning Engineer, you will be a critical member of our startup team, driving our mission to detect AI-generated images. This is an applied research role where you balance staying on top of emerging research with shipping. You're able to create models for inference that address customer needs, iterate quickly, and ship to production regularly. We seek someone who is passionate about the intersection of AI and security, capable of pushing the boundaries of what is possible.

What you’ll be working on

• Conduct novel research in AI-generated image detection, staying up to date on the latest developments in the field.
• Design, develop, and deploy machine learning models to detect AI-generated images.
• Implement scalable and efficient algorithms for real-time inference.
• Collaborate closely with cross-functional teammates to integrate models into production systems.
• Rapidly prototype and iterate on solutions based on feedback and performance metrics.
• Contribute to the overall architecture and strategic direction of our AI detection technology.
• Publish findings and contribute to the broader machine learning community via the Nuanced blog.

Requirements

• Master’s or PhD in Computer Science, Machine Learning, Artificial Intelligence, or a related field.
• Proven experience in machine learning research and model development, particularly in the area of computer vision and image processing.
• Strong publication record in top-tier conferences or journals is a plus, but not required.
• Proficiency in programming languages such as Python, and experience with ML frameworks like TensorFlow, PyTorch, or Keras.
• Strong problem-solving skills and a passion for tackling complex, previously unexplored challenges.
• Excellent communication skills and the ability to work collaboratively in a fast-paced startup environment.

About you

1. Strong sense of urgency: Building the technical foundation of a company in a competitive and high-stakes landscape requires executing and delivering high-quality solutions to customers swiftly.
2. High agency, high accountability: As an early-stage startup, the ability to be a self-starter, take ownership, and deliver results despite incomplete or uncertain requirements is crucial.
3. Adaptability: The startup environment is dynamic and ever-changing, necessitating a willingness to revisit ideas, pivot, rebuild, and evolve with the company.
4. Product focus: Ensuring alignment with business goals and meeting customer needs from the user’s perspective is essential for driving the product's success and growth.
5. Collaborative and intensely conscientious. You’re team-oriented, encouraging, and prioritize collective success over individual recognition.

Why join us

• Be a founding member of a groundbreaking startup addressing one of the most critical challenges of our age.
• Opportunity to work on cutting-edge technology and contribute to impactful research in a deep problem space.
• Competitive salary and equity package.
• Medical, dental, and vision insurance.

Why not join us

As a rapidly growing early-stage start-up, we know we're not for everyone. You should not apply if you:

• Seek comfort over challenge: If you prefer a structured, predictable work environment with well-defined tasks and minimal ambiguity, this startup role might not be suitable. Our early-stage environment requires flexibility, resilience, and a willingness to embrace uncertainty.
• Prefer limited work hours: If you are looking for a standard 9-to-5 job, this role may not be for you. Building something truly impactful requires dedication, long hours, and often going above and beyond. The commitment needed here is substantial.
• Require dependency on direct supervision: If you require constant direction and supervision to complete tasks, this role will be challenging. We need self-starters who can take initiative, identify problems, and drive solutions independently.
• Dislike candor. You can expect honest conversations regularly about what is going well, what isn’t going well, and what could be better. No surprises. We expect this honesty to flow in both directions and want to hear from you: how can the product, tools, processes, or culture be better?