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Remote Rf Filter Design Engineer Jobs in Suffolk, VA

Arctiq

Senior Site Reliability Engineer

Norfolk, VA · Remote

$55.25 - $73.25/hr

This is a remote, contract opportunity for a project Arctiq is delivering for a client. Candidates ... Design complex telemetry pipelines for full-stack observability. * Strategic Automation: Design and ...

BOOZ, ALLEN & HAMILTON, INC.

AI/ML Engineer

Hampton, VA · On-site +1

$77K - $176K/yr

Design and implement effective AI solution architecture utilizing approaches of various AI ... Remote : If this position is listed as remote, there may still be occasions when you are required ...

BOOZ, ALLEN & HAMILTON, INC.

AI/ML Engineer

Norfolk, VA · On-site +1

$77K - $176K/yr

Design and implement effective AI solution architecture utilizing approaches of various AI ... Remote : If this position is listed as remote, there may still be occasions when you are required ...

BOOZ, ALLEN & HAMILTON, INC.

AI/ML Engineer

Chesapeake, VA · On-site +1

$77K - $176K/yr

Design and implement effective AI solution architecture utilizing approaches of various AI ... Remote : If this position is listed as remote, there may still be occasions when you are required ...

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All JobsRemote Rf Filter Design Engineer JobsRemote Rf Filter Design Engineer Jobs in Suffolk, VA

Remote Rf Filter Design Engineer information

See Suffolk, VA salary details

$35.2K

$112K

$174.1K

How much do remote rf filter design engineer jobs pay per year?

As of Jun 26, 2026, the average yearly pay for remote rf filter design engineer in Suffolk, VA is $111,950.00, according to ZipRecruiter salary data. Most workers in this role earn between $92,800.00 and $132,200.00 per year, depending on experience, location, and employer.

What is the difference between Remote Rf Filter Design Engineer vs Remote RF Circuit Design Engineer?

AspectRemote Rf Filter Design EngineerRemote RF Circuit Design Engineer
Primary FocusDesigning RF filters to select or reject specific frequency bandsDesigning RF circuits including amplifiers, mixers, and oscillators
Skills & CertificationsRF filter theory, simulation tools, RF component knowledgeRF circuit design, PCB layout, RF simulation tools
Work EnvironmentElectronics or telecommunications companies, remote teamsWireless device manufacturers, remote engineering teams

The main difference is that Remote Rf Filter Design Engineers specialize in creating RF filters for signal processing, while Remote RF Circuit Design Engineers work on broader RF circuit components. Both roles require RF design expertise and often overlap, but their focus areas differ within the RF engineering field.

What are the key skills and qualifications needed to thrive as a Remote RF Filter Design Engineer, and why are they important?

To thrive as a Remote RF Filter Design Engineer, you need a solid background in electrical engineering, signal processing, and RF circuit design, typically supported by a relevant degree and experience in designing RF/microwave filters. Proficiency with design and simulation tools such as ADS, HFSS, CST, or Microwave Office, along with familiarity with PCB layout software, is essential. Strong problem-solving skills, attention to detail, and effective remote communication are crucial soft skills for collaborating with distributed teams and managing complex projects. These skills and qualities ensure precise, efficient filter designs that meet performance specifications and enable seamless teamwork in a remote environment.

What are some common challenges faced by Remote RF Filter Design Engineers, and how can they effectively collaborate with cross-functional teams?

Remote RF Filter Design Engineers often face challenges related to clear communication and coordination with hardware, PCB layout, and manufacturing teams who may be located in different time zones. To overcome these, it's important to leverage collaboration tools, maintain thorough documentation, and schedule regular virtual meetings to review design specifications, test results, and project milestones. Building strong relationships with team members and proactively addressing technical concerns can help ensure that filter designs meet both performance requirements and manufacturing constraints.

What is a Remote RF Filter Design Engineer?

A Remote RF Filter Design Engineer is a professional who specializes in designing radio frequency (RF) filters used in electronic communication devices, such as smartphones, radios, and wireless systems. They work remotely, using specialized software and tools to create, simulate, and optimize RF filter circuits that block unwanted frequencies and allow desired signals to pass. The role requires a strong background in electrical engineering, RF principles, and experience with simulation tools. Remote RF Filter Design Engineers often collaborate with teams online and may work for companies in telecommunications, defense, or consumer electronics industries.
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Remote Rf Filter Design Engineer jobs near you
AI/ML Engineer

AI/ML Engineer

Frontier Technology Inc.

Chesapeake, VA • On-site, Remote

Full-time

Posted 8 days ago

Job description

Overview
FTI Defense is seeking a hands-on AI/ML Engineer to design, build, and deploy advanced machine learning solutions supporting defense and national security missions. This role focuses on execution in oversight, ideal for an engineer who thrives in the code, enjoys building end-to-end pipelines, and takes pride in seeing their work directly impact operational systems.
FTI Defense delivers mission-focused solutions to the Department of Defense/Depratment of War (DoD/DoW) and Intelligence Community (IC) through advanced engineering, digital transformation, and program execution expertise. We help our customers solve complex challenges and achieve mission success by integrating people, process, and technology.
Responsibilities
  • Design, develop, and deploy AI/ML models and pipelines that meet mission and performance objectives.
  • Build, train, and fine-tune models using frameworks such as PyTorch, TensorFlow, scikit-learn, Hugging Face, and LangChain.
  • Develop and operationalize MLOps pipelines (MLflow, Kubeflow, DVC, or custom training/inference orchestration).
  • Implement and optimize vector databases (Milvus, Pinecone, Chroma, FAISS) and retrieval architectures (RAG, graph, hybrid).
  • Write clean, efficient Python code for data ingestion, feature engineering, embeddings, and inference services.
  • Experiment with fine-tuning and optimization of LLMs and task-specific models (LoRA, QLoRA, PEFT).
  • Contribute to agent-based applications using frameworks like LangGraph, AutoGen, CrewAI, or DSPy.
  • Integrate AI services into real-world systems via APIs, event-driven workflows, or UI copilots.
  • Collaborate with data engineers, software developers, and mission analysts to ensure AI models are production-ready and aligned with customer needs.
  • Participate in peer reviews, contribute to shared repositories, and document models and experiments for reproducibility.

Education/Qualifications
Minimum Requirements:
  • Must be a U.S. citizen and be willing to obtain and maintain a security clearance, as needed.
  • 6-10+ years of professional experience developing and deploying AI/ML solutions in production environments.
  • Minimum of 3 years' professional experience within the Department of Defense/Department of War (DoD/DoW) AI assurance, security, and deployment environments.
  • Strong Python development skills with hands-on experience building AI/ML solutions.
  • Direct experience with ML frameworks such as PyTorch, TensorFlow, scikit-learn, Hugging Face, or LangChain.
  • Proven ability to build and deploy MLOps pipelines using MLflow, Kubeflow, DVC, or equivalent.
  • Working knowledge of vector databases (Milvus, Pinecone, Chroma, FAISS) and retrieval-based architectures (RAG, hybrid, graph).
  • Professional experience fine-tuning and evaluating LLMs or smaller task-specific models using LoRA, QLoRA, or PEFT.
  • Professional experience integrating AI capabilities into production systems or mission applications.

Preferred Qualifications:
  • Familiarity with agentic frameworks (LangGraph, AutoGen, CrewAI, DSPy) and multi-agent reasoning.
  • Understanding of prompt engineering, retrieval quality, and grounding methods.
  • Exposure to GPU-based or edge inference environments.
  • Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related technical field.
  • Active Secret clearance preferred; ability to obtain one is required.

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