AI/ML Engineer

Expression Networks; Washington (District of Columbia); Hybrid; USD 140,000 - 190,000; Full time

Benefits offered by this job

401k matching

Medical/dental/vision insurance

Education reimbursement up to $10,000/

Life insurance

PTO and holidays

Onsite gym

Commuter Benefits Plan

In-office Cold Brew Coffee

Job summary

Expression seeks an experienced AI/ML Engineer to design, optimize, and evaluate ML capabilities for heterogeneous edge platforms. You will work with software engineers to develop AI pipelines for intelligent signal characterization, data prioritization, and distributed inference while managing constrained compute and bandwidth.

The ideal candidate has strong expertise in applied ML, modern LLM technologies, edge AI optimization, and production deployment of AI systems.

Qualifications

• Bachelor's degree or higher in Computer Science, Artificial Intelligence, Data Science, Electrical Engineering, Applied Mathematics, or related discipline.
• 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.

Responsibilities

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

Skills

Python programming

Production AI

Communication

Education

Bachelor's degree or higher in CS/AI/DS/EE/Math

Tools

PyTorch

LangGraph

LangChain

CrewAI

Semantic Kernel

Docker

Cloud deployment tooling

Job description

Expression is seeking an experienced AI/ML Engineer to design, optimize, and evaluate machine learning capabilities that operate efficiently on heterogeneous edge computing platforms. Working closely with software engineers, you will develop AI pipelines that enable intelligent signal characterization, data prioritization, distributed inference, and decision support while operating within constrained compute, bandwidth, and communications environments.

The ideal candidate has strong expertise in applied machine learning, modern LLM technologies, edge AI optimization, and production deployment of AI systems.

Security Clearance

Eligible to obtain Secret or Top Secret Clearance (U.S citizenship required)

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.

Required 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.

Location

Hybrid or Remote with limited travel

Benefits

• 401k matching
• PPO and HDHP medical/dental/vision insurance
• Education reimbursement up to $10,000/yr
• Complimentary life insurance
• Generous rollover PTO and 11 days of holiday leave
• Onsite gym facility and trainer
• Commuter Benefits Plan
• In-office Cold Brew Coffee

About Expression

Founded in 1997 and headquartered in Washington DC, Expression provides data fusion, data analytics, AI/ML, software engineering, information technology, and electromagnetic spectrum management solutions to the U.S. Department of Defense, Department of State, and national security community. Expression’s culture focuses on creating immediate and sustainable value for our clients via agile delivery of tailored solutions built through constant engagement with our clients. Expression was ranked #1 on the Washington Technology 2018's Fast 50 list of fastest-growing small business Government contractors and a Top 20 Big Data Solutions Provider by CIO Review.

We make sure to provide everyone with the tools and opportunities to grow while working on some of the newest technologies in the industry. We get excited about celebrating our professionals' milestones, accomplishments, promotions, overcoming challenges, and many other aspects that make an engaging collaborative environment.

Equal Opportunity Employer/Veterans/Disabled