Kopius, Inc. · 1 week ago
Machine Learning Engineer
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Information Technology
Insider Connection @Kopius, Inc.
Responsibilities
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.
Qualification
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Required
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
Preferred
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
Benefits
Competitive salary
Equity
Token-share
Flexible remote work environment
Paid company off-sites
Company
Kopius, Inc.
Kopius helps build customer-centric digital products, empowered by technology, data & AI.