Machine Learning Jobs in Web3

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Job Position Company Posted Location Salary Tags

Heretic

San Francisco, CA, United States

$84k - $120k

ZAUBAR

remote

$63k - $75k

Ripple

Toronto, Canada

$54k - $60k

Genies, Inc.

remote

$175k - $260k

DApp360 Workforce

United States

$105k - $108k

ChainGPT

Remote

$60k - $120k

Aave Companies

London, United Kingdom

$90k - $110k

Binance

Asia

Binance

Asia

Binance

Asia

Binance

Asia

Binance

Canada

Binance

Dubai, United Arab Emirates

NIL (CYPRUS) LTD

Lima, Peru

$74k - $100k

Heretic

San Francisco, CA, United States

$121k - $165k

Applied AI ML Engineer Stealth PortCo

Heretic
$84k - $120k estimated

This job is closed

Applied AI/ML Engineer (Stealth PortCo)

San Francisco /
Stealth Mode Portfolio Company /
Full-Time
/ Hybrid

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Overview of Role

Heretic Ventures is seeking an Applied AI/ML Engineer with at least 1-2 years of professional experience to join an early stage generative AI consumer business that Heretic Ventures is launching.

The ideal candidate has strong knowledge of Python, experience with generative AI model training & fine-tuning, and has worked in professional environments with engineering or AI/ML teams.  This engineer will participate in the full end to end deep learning pipeline from data collection to model deployment. You'll wear many hats, but your primary focus will be on making our AI models better (and defining what better means by setting up amazing evaluation metrics).

This is a unique opportunity to help build a billion-dollar company from the ground up while learning from successful repeat entrepreneurs and a stable of powerful and experienced mentors and advisors. 

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 ideating and launching new businesses in the creator economy, 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 both in selecting and in advising companies.

Responsibilities

    • Collaborate with cross-functional teams to train and fine-tune machine learning models and systems for consumer-focused ventures.
    • Fine-tune foundational machine learning algorithms and models for various generative AI applications, including text-to-image diffusion models, large language models, and other emerging generative AI.
    • Develop multi-model architectures to meet product & business requirements for new venture concepts.
    • Collect, preprocess, and analyze data to extract meaningful insights and improve the performance of AI models.
    • Deploy and maintain AI models in production environments, ensuring scalability, reliability, and efficiency.
    • 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.

Qualifications

    • Bachelor's or Master's degree in Computer Science, Mathematics,  Artificial Intelligence / Machine Learning, or a related field.
    • 1-2 years of professional experience working on applied AI projects, preferably in a product development or research environment.
    • 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 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 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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Heretic is an Equal Opportunity Employer committed to inclusion and diversity. We welcome people of different backgrounds, experiences, abilities and perspectives and will consider all qualified applicants for employment in accordance with all state, local, and federal laws.

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Is machine learning a good career?

Yes, machine learning is a rapidly growing field and can be a very promising career option for those interested in it

As businesses and industries increasingly rely on data to drive decision-making, there is a growing need for skilled professionals who can analyze and make sense of this data

Machine learning, which involves developing algorithms that can learn from and make predictions on large datasets, is a crucial part of this process

Machine learning careers can range from data analysts, machine learning engineers, data scientists, and more

These professionals work in a variety of industries, including finance, healthcare, e-commerce, and technology

The demand for machine learning experts is high, and the salaries in this field are also generally quite competitive

However, it's important to note that machine learning can be a complex field that requires a strong background in mathematics, statistics, and computer science

It also requires ongoing learning and staying up-to-date with the latest developments and tools in the field

If you enjoy working with data, have a strong interest in programming, and are willing to put in the effort to stay current with developments, a career in machine learning can be very rewarding.