Member of Technical Staff - Model Engineer

Member of Technical Staff - Model Engineer

Full-time | On-site

Location: San Francisco

We are seeking a founding Member of Technical Staff to join our core AI team and drive the modernization of a foundational global industry. This role offers the chance to work directly with the company's founders to define the technical direction and build AI from the ground up, combining hardware, software, and operations.

As a Model Engineer, you will be deeply involved in the entire lifecycle of model development, from research and data preparation to production deployment in real-world systems. You will play a crucial role in building the AI capabilities that enable a vertically integrated infrastructure platform.

What you'll do:

• Train end-to-end models for mission-critical applications like fault prediction, network state modeling, and autonomous repair.
• Develop multi-modal models over structured domain data, implementing function-calling capabilities for real-time network decisions.
• Build data cleaning and pipeline infrastructure necessary to support model development and scaling.
• Rigorously evaluate and benchmark model performance over both physical hardware and virtualized testing environments.
• Collaborate directly with founders to set technical direction, define the long-term AI vision, and shape the core team culture.
• Ship models into production networks and work closely with firmware and application teams to ensure seamless integration and performance.
• Be a technical leader in the effort to modernize the industry through cutting-edge AI.

Requirements

• The ideal candidate possesses a strong foundation in machine learning engineering, a bias for action, and an entrepreneurial mindset.
• 2+ years of post-academic experience in building, training, and scaling neural networks from the ground up.
• Strong background in Python and ML coding, with expert-level proficiency in frameworks like PyTorch.
• Demonstrated comfort with the full model development lifecycle, including data cleaning, pipeline building, evaluation, benchmarking, and fine-tuning.
• Experience with Neural Networks and general Machine Learning principles.
• We are open to PhD dropouts/graduates with top industry internships or significant startup experience.
• Bonus points if you have experience training Large Language Models (LLMs) and possess an entrepreneurial spirit (e.g., from founding a startup).

Work Policy:

• This is an on-site role based in our San Francisco office, requiring a minimum of three days a week in the office to foster a collaborative, mission-driven environment.

Benefits

We offer a highly competitive and structured compensation package designed to attract and retain exceptional talent, with substantial long-term growth potential.

• Target Salary Range: $200,000 - $300,000 (Base Salary).
• Total Compensation: A highly competitive package that includes a base salary and significant equity. Total compensation is benchmarked against leading AI companies.
• Equity: We offer real ownership. Our equity grants have the potential for substantial growth, with projections of 10-15x multiples over the next four years. For exceptional talent, the initial equity grant has the potential to be worth $15M+ based on projected growth.
• Flexibility: We are flexible and can adjust the cash/equity split for the right candidate, and there is no strict cap for exceptional talent.
• Relocation/Visa Support: Visa sponsorship is available, and we work with an excellent law firm to facilitate the process.

Due to the high volume of applications we anticipate, we regret that we are unable to provide individual feedback to all candidates. If you do not hear back from us within 4 weeks of your application, please assume that you have not been successful on this occasion. We genuinely appreciate your interest and wish you the best in your job search.

Commitment to Equality and Accessibility:

At MLabs, we are committed to offer equal opportunities to all candidates. We ensure no discrimination, accessible job adverts, and providing information in accessible formats. Our goal is to foster a diverse, inclusive workplace with equal opportunitie