Hatch IT

AI/ML Engineer

Rol remoto de AI ML Engineering con fit claro de ubicación del candidato.

Publicado13 jul 2026

Países elegibles1 país aceptado

Señal de senioritySenior

Modelo de trabajoRemoto

Ubicaciones aceptadas para candidatos

Estados Unidos

Docker LLM Python

Resumen del rol

AI/ML Engineer

Requisitos y responsabilidades

Contenido del rol extraído en secciones para revisar más rápido.

Responsibilities:

Design and implement AI capabilities supporting intelligent data characterization, classification, prioritization, and decision support.
Evaluate, optimize, and deploy open-weight foundation models appropriate for resource-constrained edge environments.
Develop efficient inference pipelines supporting heterogeneous compute environments ranging from embedded processors to workstation-class systems.
Implement Retrieval-Augmented Generation (RAG), semantic search, and knowledge retrieval capabilities where appropriate.
Design AI orchestration workflows supporting distributed inference across multiple edge devices.
Develop evaluation methodologies for AI accuracy, latency, resource utilization, and operational performance.
Implement model monitoring, observability, testing, and automated evaluation frameworks.
Collaborate with software engineers to integrate AI models into production software platforms.
Optimize models using quantization, pruning, distillation deployment technologies.
Support experimentation involving multimodal data sources, sensor-derived features, and structured mission data.
Develop AI governance practices including model evaluation, explainability, responsible AI, and secure deployment.
Document model development, evaluation results, and technical recommendations.
Support customer demonstrations and prototype evaluations.

Details

Design and implement AI capabilities supporting intelligent data characterization, classification, prioritization, and decision support.
Evaluate, optimize, and deploy open-weight foundation models appropriate for resource-constrained edge environments.
Develop efficient inference pipelines supporting heterogeneous compute environments ranging from embedded processors to workstation-class systems.
Implement Retrieval-Augmented Generation (RAG), semantic search, and knowledge retrieval capabilities where appropriate.
Design AI orchestration workflows supporting distributed inference across multiple edge devices.
Develop evaluation methodologies for AI accuracy, latency, resource utilization, and operational performance.
Implement model monitoring, observability, testing, and automated evaluation frameworks.
Collaborate with software engineers to integrate AI models into production software platforms.
Optimize models using quantization, pruning, distillation deployment technologies.
Support experimentation involving multimodal data sources, sensor-derived features, and structured mission data.
Develop AI governance practices including model evaluation, explainability, responsible AI, and secure deployment.
Document model development, evaluation results, and technical recommendations.
Support customer demonstrations and prototype evaluations.
Bachelor degree in Computer Science, Artificial Intelligence, Data Science, Electrical Engineering, Applied Mathematics, or related discipline. An advanced degree is preferred.
5-8+ years of professional experience developing production AI or machine learning applications.
Strong Python programming experience.
Experience with PyTorch.
Experience deploying LLMs in production environments.
Experience with LangGraph, LangChain, CrewAI, Semantic Kernel, or similar orchestration frameworks.
Experience implementing Retrieval-Augmented Generation (RAG).
Experience with vector databases and semantic search.
Experience deploying AI models on edge or resource-constrained devices.
Experience with model optimization techniques including quantization, model compression, or inference acceleration.
Experience designing evaluation frameworks for AI systems.
Experience with Docker and cloud-native AI deployment.
Excellent communication and collaboration skills.
Experience applying AI to sensor analytics, time-series data, or signal processing.
Experience with software-defined radio data, RF analytics, or geospatial data analytics.
Experience developing multimodal AI applications.
Experience deploying AI across distributed edge computing environments..
Experience supporting DoD, Intelligence Community, or Federal customers.
Experience working in bandwidth-constrained or disconnected operational environments.
Experience supporting National Security or Federal Civilian customers.

Qualifications:

Bachelor degree in Computer Science, Artificial Intelligence, Data Science, Electrical Engineering, Applied Mathematics, or related discipline. An advanced degree is preferred.
5-8+ years of professional experience developing production AI or machine learning applications.
Strong Python programming experience.
Experience with PyTorch.
Experience deploying LLMs in production environments.
Experience with LangGraph, LangChain, CrewAI, Semantic Kernel, or similar orchestration frameworks.
Experience implementing Retrieval-Augmented Generation (RAG).
Experience with vector databases and semantic search.
Experience deploying AI models on edge or resource-constrained devices.
Experience with model optimization techniques including quantization, model compression, or inference acceleration.
Experience designing evaluation frameworks for AI systems.
Experience with Docker and cloud-native AI deployment.
Excellent communication and collaboration skills.

Preferred Qualifications:

Experience applying AI to sensor analytics, time-series data, or signal processing.
Experience with software-defined radio data, RF analytics, or geospatial data analytics.
Experience developing multimodal AI applications.
Experience deploying AI across distributed edge computing environments..
Experience supporting DoD, Intelligence Community, or Federal customers.
Experience working in bandwidth-constrained or disconnected operational environments.
Experience supporting National Security or Federal Civilian customers.