AI/ML Engineer

This is a fully remote position, open to applicants in Washington.

📋 Description

• Create and execute AI functionalities that enhance intelligent data characterization, classification, prioritization, and decision-making support.

• Assess, refine, and implement open-weight foundation models suitable for resource-limited edge environments.

• Construct efficient inference pipelines that cater to diverse computing environments, from embedded processors to workstation-class systems.

• Incorporate Retrieval-Augmented Generation (RAG), semantic search, and knowledge retrieval features where applicable.

• Develop AI orchestration workflows that facilitate distributed inference across various edge devices.

• Establish evaluation methods for assessing AI accuracy, latency, resource usage, and operational efficiency.

• Set up model monitoring, observability, testing, and automated evaluation frameworks.

• Work closely with software engineers to embed AI models into production software platforms.

• Enhance models through quantization, pruning, and distillation deployment techniques.

• Assist in experimentation involving multimodal data sources, sensor-derived features, and structured mission data.

• Formulate AI governance practices that include model assessment, explainability, responsible AI, and secure deployment.

• Document the development of models, evaluation outcomes, and technical suggestions.

• Aid in customer demonstrations and prototype assessments.

⛳️ Requirements

• Bachelor’s degree in Computer Science, Artificial Intelligence, Data Science, Electrical Engineering, Applied Mathematics, or a related field. An advanced degree is preferred.

• 5-8+ years of professional experience in developing production-level AI or machine learning applications.

• Proficient in Python programming.

• Familiarity with PyTorch.

• Experience in deploying LLMs within production contexts.

• Knowledge of orchestration frameworks such as LangGraph, LangChain, CrewAI, Semantic Kernel, or similar.

• Practical experience with implementing Retrieval-Augmented Generation (RAG).

• Understanding of vector databases and semantic search.

• Experience in deploying AI models on edge or resource-constrained devices.

• Proficiency in model optimization strategies, including quantization, model compression, or inference acceleration.

• Experience in designing evaluation frameworks tailored for AI systems.

• Familiarity with Docker and cloud-native AI deployment methodologies.

• Exceptional communication and teamwork abilities.

🏝️ Benefits

• 401k matching

• PPO and HDHP medical/dental/vision insurance

• Education reimbursement up to $10,000 per year

• Complimentary life insurance

• Generous PTO along with 11 days of holiday leave

• Access to onsite gym facility and personal trainer

• Commuter Benefits Plan

• In-office Cold Brew Coffee