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Niche neuro-symbolic specialization, non-metro location, and lesser-known employer lower competition.
Specialized neuro-symbolic ML research focus limits transferability across industries.
Explicit 4+ years requirement plus specialized neuro-symbolic skills and tool mandates enforce strict shortlisting.
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Develop neuro-symbolic AI architectures combining neural perception and language components with symbolic reasoning modules.
Integrate symbolic programming languages (Prolog, Datalog, etc.) into PyTorch or JAX pipelines to enforce structural constraints and enable auditability.
Translate research into working prototypes addressing real enterprise problems rather than academic benchmarks.
Minimum 4 years of relevant research or engineering experience in AI/ML, specifically at the neural-symbolic interface.
Strong background in at least one area: differentiable programming, neural theorem proving, logic-augmented LLMs, probabilistic logic, or constrained generation.
Familiarity with logic programming languages such as Prolog, Datalog, or Answer Set Programming.
Experience integrating symbolic modules with neural frameworks like PyTorch or JAX.
Senior researcher or engineer proficient in blending symbolic reasoning with neural networks for practical AI solutions.
Experienced in translating research ideas into enterprise-grade prototypes beyond academic benchmarks.
Comfortable working with both probabilistic and logic-based AI models integrating symbolic and neural paradigms.