Machine Learning Jobs in Web3

239 jobs found

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Job Position Company Posted Location Salary Tags

Entangle Labs

Dubai, United Arab Emirates

$84k - $106k

Brave

London, United Kingdom

$84k - $108k

Whatnot

San Francisco, CA, United States

$205k - $275k

Binance

Abu Dhabi, United Arab Emirates

Launchpadtechnologiesinc

Remote

$126k - $127k

MoonPay

Barcelona, Spain

$126k - $127k

Bluesky

Remote

$115k - $180k

Bluesky

Remote

$123k - $180k

Truflation

Remote

$90k - $180k

Truflation

Remote

$105k - $180k

Truflation

Remote

$43k - $54k

Heretic/Arcade

San Francisco, CA, United States

$21k - $70k

Genies

San Mateo, Portugal

$165k - $230k

Brave

London, United Kingdom

$18k - $80k

Entangle Labs
$84k - $106k estimated

ML Ops Engineer

Dubai
Tech & Product /
Remote

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Entangle is reshaping the blockchain landscape with advanced interoperability and data connectivity solutions. By creating a seamless framework for DApps to interact across various networks, we’re solving one of blockchain’s biggest challenges: the barriers between fragmented ecosystems. Our Photon Messaging Protocol, universal data feeds, and customizable agent network bring high-performance, scalable infrastructure to developers in the DeFi space and beyond. 

We are currently seeking an experienced ML Ops engineer with experience in AI projects to join our team.

Key Responsibilities:
Model Deployment
Dockerize and deploy multi-agent LLM instances, ensuring compatibility with LangGraph pipelines.
Optimize model serving for low-latency, high-throughput applications, leveraging GPU/TPU resources efficiently.
Implement scalable model deployment strategies for concurrent multi-agent tasks.
Monitoring and Logging
Establish end-to-end monitoring for the AI platform, tracking system health, latency, and failure rates
Monitor LLM-specific metrics such as token latency, memory consumption, and prompt-response accuracy.
Develop drift detection mechanisms for model inputs and outputs to ensure sustained performance.
Pipeline Automation
Automate training, evaluation, and deployment workflows for LangGraph-enabled pipelines.
Build and maintain CI/CD pipelines for integrating multi-agent frameworks with backend services.
Automate versioning and rollback mechanisms for LLMs, ensuring seamless updates.
Infrastructure Management
Collaborate with DevOps teams to scale Kubernetes clusters for LangGraph chains and WebSocket-heavy APIs.
Optimize resource allocation for shared GPU/TPU inference loads across agents.
Implement caching strategies for high-reuse LLM queries and shared agent tools.
Collaboration and Documentation
Document multi-agent system workflows, LangChain integration, and API usage for internal and external stakeholders.
Collaborate with backend engineers to align model endpoints with application requirements and QA teams to resolve deployment issues.
Provide guidelines for extending LangGraph tools and chains with custom agent implementations.

Qualifications:
Experience deploying (Ray Serve/vllm/...) and optimizing (quantization/ONNX/...) LLMs in production (e.g., OpenAI, HuggingFace models).
Proficiency with containerization (Docker) and orchestration (Kubernetes, Helm).
Familiarity with LangChain, Web3 tools, or multi-agent systems is a strong plus.
Strong understanding of CI/CD tools (e.g., GitHub Actions, Jenkins).
Excellent communication skills and ability to document complex systems clearly.

What we offer:
- Exciting growing international start-up with ambitious goals of making headways in a revolutionary, multi-billion dollar industry
- Pay in USDT
- Scrum/agile environment
- Highly skilled engineering team
- Attractive compensation plus token allocations
- Remote work in a timezone that corresponds well with the UAE time
- Paid vacation and public holidays.
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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.