Machine Learning Engineer
Remote
Vanna Labs
What we are building
Vanna Labs is building native on-chain AI inference, designed to deliver seamless and scalable inference secured by state-of-the-art cryptography. The Vanna Network is an EVM blockchain network that is a composable execution layer for on-chain AI. The network features access to scalable and secure model inference, allowing developers to seamlessly leverage AI models in composable smart contracts to create powerful decentralized applications and enable new use-cases.
Who we are
Our team is made up of experienced engineers from companies like Two Sigma, Palantir and Google, dedicated to driving the next generation of decentralized AI use-cases on the blockchain.
Join us on our mission to decentralize AI!
The Role
We are seeking a self-driven and motivated Machine Learning Engineer with a specialized focus on building robust infrastructure tailored for handling large-scale inference workloads for AI and ML models. You will spearhead the design, development, and optimization of high-performance AI/ML systems capable of supporting real-time and batch processing requirements across diverse domains. You will collaborate closely with cross-functional teams to architect and implement cutting-edge inference pipelines and infrastructure, ensuring the reliability, efficiency, and scalability of our machine learning model deployments. Your responsibilities will include:
Design and implement scalable and efficient machine learning inference infrastructure and architecture to support real-time and batch processing requirements.
Develop deployment pipelines and tools for deploying machine learning models into production environments, including containerization (e.g., Docker) and orchestration (e.g., Kubernetes).
Optimize model inference performance and resource utilization through techniques such as model quantization, pruning, and acceleration (e.g., GPU/TPU utilization, model caching).
Continuously evaluate and improve the performance of machine learning models and infrastructure through experimentation and optimization techniques.
Qualifications
Bachelor's or Master's degree in Computer Science, Engineering, Mathematics, or a related field
Strong background in machine learning, deep learning, and statistical modeling with hands-on experience in developing and deploying ML infrastructure
Proficiency in programming languages such as Python, Java, C++, Go
Extensive experience with popular ML frameworks (e.g., TensorFlow, PyTorch, HuggingFace) and technologies (e.g. CUDA, ONNX)
Experience as a software engineer with deep understanding of algorithms and data structures
Have familiarity with the latest AI and ML research and working knowledge of how these systems are efficiently implemented.
Nice to have
Familiarity with MLOps, DataOps
Experience at fast-growing startups or companies
Interest in blockchain technology and its benefits such as privacy, computational integrity and censorship-resistance
Experience supporting ML or AI Infrastructure, such as Triton
Why work with us
You’ll build cutting-edge infrastructure that will define the future of blockchain and AI
You’ll receive competitive salary, equity, and token-share
You’ll be part of a flat, results-driven organization with room for leadership and growth
You'll work with a passionate team of engineers and researchers
You’ll make impactful contributions from day one as an early engineer
Flexible remote work environment with top benefits
Paid company off-sites
Join us at Vanna Labs and be part of a team dedicated to revolutionizing decentralized AI on the blockchain. If you are passionate about technology, innovation, and shaping the future, we want to hear from you. Apply now and help us build the next generation of decentralized applications powered by AI.
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Architecture Blockchain Computer Science CUDA DataOps Deep Learning Docker Engineering GPU HuggingFace Java Kubernetes Machine Learning Mathematics ML infrastructure ML models MLOps Model inference ONNX Pipelines Privacy Python PyTorch Research Statistical modeling Statistics TensorFlow
Perks/benefits: Career development Competitive pay Equity Flex hours Flex vacation Startup environment
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