Machine Learning Jobs in Web3

248 jobs found

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Job Position Company Posted Location Salary Tags

Overclock Labs

Austin, TX, United States

$100k - $110k

Genies

Remote

$90k - $118k

Zscaler

Remote

$126k - $127k

Whatnot

New York, NY, United States

$180k - $285k

Coinbase

Remote

$126k - $127k

Zinnia

Remote

$126k - $131k

Immunefi

Remote

$126k - $127k

Zscaler

Remote

$122k - $127k

Zinnia

Remote

$126k - $131k

Inmobi

Remote

$122k - $150k

Coinbase

Remote

$180k - $212k

Zscaler

Remote

$147k - $210k

Coinbase

Remote

$186k - $218k

Coinbase

Remote

$191k

CEF ai

San Francisco, CA, United States

$80k - $250k

Overclock Labs
$100k - $110k
Austin, Texas
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Account Executive – GPU Cloud Infrastructure (AI/ML Focus)

Austin, Texas
Marketing /
Full-time /
Remote

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Akash Network is the world’s first open-source, decentralized cloud—built for the high-demand workloads of AI and machine learning. We connect GPU providers with users seeking affordable, scalable compute infrastructure—without the constraints of centralized cloud pricing and capacity.

As AI companies scale rapidly, Akash offers a cost-effective, performant, and open alternative to traditional cloud platforms. We’re growing fast and looking for a high-performing Sales Representative to help drive this next phase.

What You Will Do:

    • Own and convert qualified inbound leads (>$5K/month GPU renters)
    • Identify and prospect high-potential AI/ML companies for outbound outreach
    • Build and manage a pipeline of opportunities from first touch to close
    • Run discovery calls, product demos, and coordinate onboarding
    • Collaborate with the growth, partnerships, and technical teams to align efforts
    • Provide feedback to inform go-to-market strategy, pricing, and positioning
    • Track activity and performance metrics using CRM tools

What we are looking for:

    • 3–5+ years of B2B sales experience, ideally in cloud, AI/ML, or DevInfra
    • Proven success closing mid- to high-value accounts ($5K+/mo deals)
    • Strong understanding of cloud infrastructure, GPUs, and AI workloads
    • Comfortable running outbound campaigns and owning revenue targets
    • Startup-minded: self-driven, scrappy, and highly adaptable
    • Excellent communication and relationship-building skills

Why Overclock Labs:

    • Shape the future of decentralized cloud and democratized compute
    • Work at the intersection of AI and Web3 innovation
    • Competitive base salary with uncapped commissions
    • Remote-first culture with a high-performance, collaborative team
$100,000 - $110,000 a year
This role has uncapped commission.
Ready to drive the future of cloud infrastructure? Apply now and help leading AI companies access the compute they need—at a fraction of the cost.
Apply for this job

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.