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Senior AI Inference Engineer (100% Remote) - Job Opportunity at Tether Operations Limited

Lugano, Switzerland
Full-time
Senior
Posted: July 12, 2025
Remote
USD 180,000 - 280,000 per year. Senior AI Inference Engineers with expertise in edge deployment and LLM optimization command premium salaries, particularly in fintech companies. The remote nature and specialized skill requirements, combined with Tether's position as a market leader in stablecoins, likely places this role at the higher end of the range, potentially reaching USD 300,000+ with equity and performance bonuses.

Key Responsibilities

Lead the deployment of machine learning models to edge devices using cutting-edge frameworks such as Llama.cpp, ONNX, TVM, MLC LLM, and IREE (MLIR), directly impacting the accessibility and performance of AI solutions across diverse hardware platforms
Drive strategic collaboration with research teams to accelerate the transition of experimental models from research environments to production-ready systems, ensuring seamless integration and optimal performance in real-world applications
Spearhead the integration of advanced AI features into existing product ecosystems, enhancing user experience and competitive positioning through the implementation of state-of-the-art machine learning capabilities

Requirements

Education

A degree in Computer Science, AI, Machine Learning, or a related field

Experience

Senior level with solid track record in AI R&D

Required Skills

Excellent programming skills in Python, and a solid understanding of C/C++ Experience with platforms such as Llama.cpp, ONNX, TVM, MLC LLM, and IREE (MLIR), which facilitate the deployment of models to specific GPU architectures Experience in NLP, transformers, fine-tuning, computer vision, TensorFlow, PyTorch, JAX and CUDA toolkit Experience working with LLMs, fine tuning, RAG, transformers is a plus Demonstrated ability to rapidly assimilate new technologies and techniques
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Sauge AI Market Intelligence

Industry Trends

The AI inference market is experiencing unprecedented growth driven by the proliferation of edge computing and the need for real-time AI processing capabilities. Organizations are increasingly moving away from cloud-only AI solutions toward hybrid architectures that combine cloud training with edge inference, creating massive demand for engineers who can optimize models for deployment across diverse hardware platforms from mobile devices to specialized inference chips. Large Language Models (LLMs) and generative AI applications are driving a fundamental shift in how AI systems are architected, with companies racing to develop more efficient inference engines that can run sophisticated models on resource-constrained devices. This trend is particularly accelerated by privacy concerns and latency requirements that make edge deployment essential for competitive AI products. The convergence of blockchain technology and AI is creating new paradigms for decentralized AI systems, where inference capabilities are distributed across networks rather than centralized in traditional cloud infrastructure. This intersection is particularly relevant in fintech where privacy, security, and decentralization are paramount concerns for users and regulators alike.

Role Significance

Typically leads a team of 3-5 engineers including ML engineers, backend developers, and DevOps specialists focused on AI infrastructure. The role involves close collaboration with research teams of 8-12 scientists and product teams of 4-6 members, requiring strong cross-functional leadership and communication skills to coordinate complex AI product development initiatives.
This is a senior individual contributor role with significant technical leadership responsibilities. The position requires making architectural decisions that directly impact product performance and user experience across Tether's entire AI platform. The role involves mentoring junior engineers and driving technical strategy for AI model deployment, positioning the engineer as a key technical leader within the organization's AI initiatives.

Key Projects

Development of proprietary AI inference engines optimized for cryptocurrency trading and risk assessment applications, requiring real-time processing capabilities and sub-millisecond latency requirements Implementation of privacy-preserving AI models for financial data analysis that comply with global regulatory requirements while maintaining high performance on edge devices Creation of scalable AI model deployment pipelines that can handle continuous integration and deployment of updated models across thousands of edge devices in Tether's global infrastructure network

Success Factors

Deep technical expertise in model optimization and quantization techniques is crucial for success, as the role requires reducing model size and computational requirements by 10-100x while maintaining accuracy for deployment on resource-constrained devices Strong collaborative skills and the ability to translate complex technical concepts to non-technical stakeholders are essential, as the role involves working with product managers, business leaders, and external partners to define AI product requirements and capabilities Proven track record of taking AI models from research prototypes to production systems serving millions of users, with experience in handling the scalability, reliability, and performance challenges that arise when deploying AI at enterprise scale Understanding of financial markets and cryptocurrency ecosystems provides significant advantage, as the role requires developing AI solutions that understand the unique requirements and constraints of digital asset trading and management

Market Demand

Extremely High. The combination of AI inference expertise and edge deployment capabilities represents one of the most sought-after skill sets in the current market. The shortage of engineers who can effectively bridge the gap between research and production deployment, particularly for LLMs and computer vision models, has created a highly competitive talent landscape where companies are willing to pay premium salaries and offer significant equity packages.

Important Skills

Critical Skills

Python and C++ programming expertise is absolutely essential as these languages form the backbone of AI model deployment and optimization workflows. Python provides the flexibility needed for rapid prototyping and integration with ML frameworks, while C++ knowledge is crucial for optimizing inference engines and achieving the performance requirements needed for edge deployment. Deep understanding of edge deployment frameworks like Llama.cpp, ONNX, TVM, and IREE represents the core technical competency for this role. These platforms are the primary tools for converting trained models into optimized inference engines that can run efficiently on diverse hardware architectures from mobile processors to specialized AI chips. Experience with transformer architectures and LLMs is critical given the current AI landscape where these models dominate most AI applications. Understanding how to optimize these complex models for inference while maintaining their capabilities is a rare and highly valued skill that directly impacts product performance and user experience.

Beneficial Skills

CUDA programming and GPU optimization skills provide significant value for developing custom inference kernels and achieving maximum performance on NVIDIA hardware, which remains dominant in AI inference applications Understanding of quantization techniques and model compression methods becomes increasingly important as AI models grow larger while deployment targets become more resource-constrained Knowledge of blockchain technology and cryptocurrency systems, while not explicitly required, provides valuable context for understanding the unique requirements and constraints of financial AI applications in the decentralized finance ecosystem

Unique Aspects

This role offers the rare opportunity to work at the intersection of cryptocurrency, AI, and edge computing, developing solutions that could reshape how financial AI systems operate in a decentralized world
Access to massive real-world financial transaction data provides unique opportunities for developing and testing AI models on datasets that most engineers never encounter
The combination of Tether's financial resources and technical ambitions creates an environment where engineers can pursue moonshot AI projects without the typical resource constraints found in traditional tech companies
Working on AI systems that directly impact global financial infrastructure provides exposure to challenges around reliability, security, and scale that few other roles can match

Career Growth

Progression to Principal Engineer level typically occurs within 2-3 years with demonstrated impact on product performance and team leadership. Management track positions become available within 3-5 years, while C-level or co-founder opportunities typically require 5-7 years of experience in senior technical roles with proven track record of scaling AI systems and leading technical teams.

Potential Next Roles

Principal AI Engineer or Staff Engineer roles focusing on AI platform architecture and cross-functional technical leadership across multiple product lines AI Engineering Manager positions leading teams of 15-25 engineers responsible for AI infrastructure and model deployment across enterprise-scale systems Chief Technology Officer or VP of Engineering roles in AI-focused fintech companies, leveraging deep technical expertise and understanding of both AI and financial markets Technical co-founder opportunities in AI startups, particularly those focused on edge AI, privacy-preserving machine learning, or decentralized AI systems

Company Overview

Tether Operations Limited

Tether Operations Limited is the company behind USDT, the world's most widely used stablecoin with over $80 billion in market capitalization. The company has expanded beyond stablecoins into a diversified technology conglomerate with investments in AI infrastructure, sustainable energy, and peer-to-peer communications. Tether's strategic position in the cryptocurrency ecosystem provides unique access to massive transaction data and the financial resources to pursue ambitious AI projects.

Tether holds a dominant position in the stablecoin market with USDT accounting for approximately 70% of all stablecoin transactions globally. The company's expansion into AI infrastructure through investments in companies like Northern Data demonstrates their commitment to becoming a major player in the AI space, leveraging their financial strength and technical expertise to compete with established tech giants.
Based in Lugano, Switzerland, Tether benefits from favorable regulatory environment and proximity to European financial markets while maintaining global operations. The company's remote-first culture and international team structure provide access to top talent worldwide, while their Swiss headquarters offers stability and regulatory clarity for both cryptocurrency and AI operations.
Tether operates as a lean, fast-moving organization that emphasizes innovation and technical excellence. The company's remote-first culture attracts top global talent and provides flexibility, while their position as market leaders in stablecoins creates an environment where engineers can work on cutting-edge problems with significant real-world impact affecting millions of users globally.
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