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Selected role

Senior AI / ML Engineer (Stealth PortCo)

Heretic San Francisco

$96k - $120k Senior Full-time

Overview of Role

We are seeking an experienced AI/ML Engineer to found a new GenAI consumer media platform, working alongside CEO Irfan Manji. Irfan is a veteran consumer product leader, with a history of successful 0-to-1 product launches at Meta (Instagram) and Zillow. The company is funded by Heretic Ventures.

The ideal candidate has deep experience training, deploying and maintaining ML models at scale for consumer products. They are curious and excited about generative AI - ideally with experience fine-tuning image models (e.g. Stable Diffusion). They will stay up-to-date with the latest advancements in AI technologies, and partner strategically with the CEO to apply those technologies to innovative new consumer applications and features. This person will be comfortable with building and maintaining the data architecture to procure and pre-process data for model training.

This is a unique opportunity to help build a billion-dollar company from the ground up while learning from successful repeat entrepreneurs, product leaders, and a bench of powerful and experienced mentors and advisors. While we prefer a permanent founding engineer, we are open to discussing a contract role - please approach us to discuss.

This is a hybrid role with the expectation of 3 days per week in-person in our sunny Presidio, SF office. The position is compensated with salary, benefits, and equity.

About Heretic

Heretic Ventures is a San Francisco-based venture studio launching new consumer businesses, including those that capitalize on AI/ML technology. Heretic is run by Managing Partner Mariam Naficy, who founded and built the pioneering internet companies Minted and Eve.com. Heretic is backed by household names in Silicon Valley (investors and entrepreneurs), who act as the studio’s advisors.

Responsibilities

Collaborate closely with the CEO (as part of the founding team) to develop product strategy, scope AI needs, and build MVPs that can be rapidly deployed for testing
Train, deploy and maintain AI models in production environments, ensuring scalability, reliability, and efficiency.
Build and maintain data architecture that procures and pre-processes data for model training.
Stay up-to-date with the latest advancements in AI technologies and research, and apply them to enhance the performance and capabilities of our ventures.
Communicate complex AI concepts and solutions effectively to both technical and non-technical stakeholders.
Be aware of different and recommend options for implementing, developing, or tuning the models that are needed to drive the various business ideas

Qualifications

Bachelor's or Master's degree in Computer Science, Mathematics, Artificial Intelligence / Machine Learning, or a related field.
5+ years of professional experience working on applied AI projects, preferably in a product development or research environment.
Experience building consumer-facing products, including partnering with full-stack & front-end eng to tie AI/ML infrastructure to a scaled front-end experience.
Strong knowledge of Python, with experience in popular machine learning libraries (e.g., TensorFlow, PyTorch).
Solid understanding of machine learning concepts and algorithms.
Experience with training and fine-tuning AI models and working with large-scale training datasets.
Proficiency in data preprocessing, feature engineering, and exploratory data analysis.
Familiarity with cloud platforms (e.g., AWS, Azure, Google Cloud) and experience with deploying AI models in cloud-based environments.
Excellent problem-solving and analytical thinking skills, with a strong attention to detail.
Effective communication and teamwork abilities, with the capacity to work in a fast-paced, collaborative environment.

Nice to Haves

Experience fine-tuning Stable Diffusion models for specific product use cases.
Experience with ML-based content ranking.
Experience fine-tuning OpenAI GPT models for specific product use cases.
Contributions to open-source AI projects or publications in relevant conferences or journals.

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