Latest ML Engineering jobs at OPSWAT

Leads production deployment and optimization of large language models on GPU hardware, focusing on quantization, inference engines, serving infrastructure, and performance benchmarking. Requires a bachelor's degree and 5+ years of software engineering experience in ML infrastructure, LLM inference, or model optimization.

Senior machine learning engineer owning cybersecurity detection capabilities end to end, from data pipelines and experimentation through production deployment and monitoring. Requires 3+ years of applied ML experience, strong Python and deep-learning skills, and demonstrated model delivery in customer-facing systems.

The Machine Learning Engineer will train and fine-tune models, build evaluation suites, analyze model failures, and improve dataset and training quality. The role requires at least two years of ML engineering or applied data science experience, strong Python skills, and practical model evaluation expertise.

Build and integrate AI/LLM capabilities for a customer and partner portal, including RAG, agents, retrieval systems, and evaluation pipelines. The role requires 3+ years of AI/ML engineering experience, strong Python skills, and production experience serving and evaluating LLMs.

Build and ship locally hosted language-model capabilities for a cybersecurity product, owning training data, fine-tuning, evaluation, security, and constrained-hardware inference. The role requires strong Python, LLM serving and grounding experience, with Rust and cybersecurity knowledge valued.

Build production AI applications, agentic workflows, backend services, and enterprise integrations for Finance. The role requires 5+ years of production software engineering experience, strong Python and backend fundamentals, and experience with scalable, secure distributed systems.

Leads the end-to-end development, deployment, and optimization of machine learning models for cybersecurity and malware detection. The role requires 5+ years of production machine learning experience, strong Python and ML framework expertise, and technical leadership across data, evaluation, and MLOps workflows.