Founding Machine Learning Engineer

webAI; United States; Remote; USD 100,000 - 150,000; Full time

Job summary

Join a stealth startup as a founding Machine Learning Engineer, where you will have a significant impact on shaping the product and technology. Work in a fast-paced environment, delivering personalized user experiences through cutting-edge ML models while collaborating closely with an experienced team in a remote-first workplace.

Benefits

Competitive salary and equity stake

Remote-first workplace

Opportunity to grow into a leadership role

Qualifications

• 3+ years of experience in building and deploying ML models in production.
• Strong proficiency in Python and experience with ML frameworks like Pytorch or Tensorflow.
• Experience with LLMs and familiarity with personalization and recommendation systems.

Responsibilities

• Design, build, and deploy ML models for user experience in personalization and recommendation.
• Develop scalable data pipelines for large-scale model development.
• Collaborate with product and engineering teams on ML-driven features.

Skills

Python

Machine Learning frameworks (Pytorch, Tensorflow)

Natural Language Processing (NLP)

Data Structures

Algorithms

Software Engineering Best Practices

Cloud Platforms (AWS, GCP, Azure)

Containerization (Docker, Kubernetes)

Collaboration

Education

Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field

Job description

About Us

We’re a stealth startup on a mission to redefine how people interact with AI in their daily lives. Our consumer-facing platform leverages cutting-edge machine learning to deliver deeply personalized, real-time experiences.

As a founding ML engineer, you’ll join a small, high-caliber team where your contributions will directly shape our product and technology stack. This is a fast-paced, builder-centric environment ideal for someone who thrives on ownership, rapid iteration, and solving hard problems at the frontier of AI.

What You’ll Do:

- Design, build, and deploy ML models that power our core user experience—particularly in areas like personalization, recommendation, and conversational AI
- Develop scalable data pipelines and training workflows for large-scale model development

- Fine-tune and optimize foundation models using techniques like LoRA, adapters, quantization, and distillation

- Collaborate cross-functionality with product and engineering to rapidly prototype and iterate on ML-driven features

- Own the full ML lifecycle—from research and experimentation to deployment and monitoring in full production
- Stay current with the latest ML research and apply it pragmatically to improve product performance and user experience

What We’re Looking For:

- 3+ years of experience building and deploying ML models in production environments

- Strong proficiency in Python and ML frameworks such as Pytorch or Tensorflow

- Experience with LLMs and NLP techniques; familiarity with personalization and recommendation systems is a plus
- Solid understanding of data structures, algorithms, and software engineering best practices
- Experience with cloud platforms (AWS, GCP, or Azure) and containerization tools like Docker and Kubernetes
- Excellent communication skills and a collaborative mindset

- Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field

Bonus Points:

- Experience in a startup environment, especially as an early or founding team member

- Contributes to open-source ML projects or strong personal portfolio
- Familiarity with MLOps practices and tools for model monitoring and deployment

- Publications or presentations in ML conferences or journals

Why Join Us:

- Be a core contributor to a product that aims to impact millions of users

- Work alongside a team of passionate, experienced professionals in a collaborative environment
- Enjoy the flexibility of a remote-first workplace
- Receive a competitive salary and meaningful equity stake in the company

- Opportunity to grow into a leadership role as the company scales

How to Apply

Fill out our application form on Ashby, or send your resume and a brief cover letter directly to us at [e-mail].