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Remote Rf Optimization Engineer Jobs in Alabama (NOW HIRING)

Confluent

Senior Software Engineer II

Montgomery, AL · On-site +1

$197K - $232K/yr

Remote Department Engineering Compensation: $197.4K - $232K • Offers Equity At Confluent, we are ... optimization for scale. * A track record of technical leadership: driving projects, influencing ...

Hewlett Packard Enterprise

Network Systems Engineering Manager (Pre-Sales) This role has been designated as 'Remote/Teleworker ... optimum organizational performance, and a highly motivated presales force. * Understands business ...

Hewlett Packard Enterprise Development LP

Network Systems Engineering Manager (Pre-Sales) This role has been designated as 'Remote/Teleworker ... optimum organizational performance, and a highly motivated presales force. * Understands business ...

Hewlett Packard Enterprise Development LP

Network Systems Engineering Manager (Pre-Sales) This role has been designated as 'Remote/Teleworker ... optimum organizational performance, and a highly motivated presales force. * Understands business ...

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Remote Rf Optimization Engineer information

What is the difference between Remote Rf Optimization Engineer vs Remote Wireless Network Engineer?

AspectRemote Rf Optimization Engineer

The Remote Rf Optimization Engineer focuses on optimizing radio frequency performance for wireless networks, primarily working on signal quality, interference reduction, and network efficiency. The Remote Wireless Network Engineer also works on wireless systems but has a broader scope, including network design, deployment, and troubleshooting of entire wireless infrastructures. Both roles require knowledge of RF principles and certifications like CWNP, but the Optimization Engineer emphasizes fine-tuning existing networks, while the Network Engineer handles overall network setup and maintenance.

What is a Remote RF Optimization Engineer?

A Remote RF Optimization Engineer is a telecommunications professional who specializes in analyzing, optimizing, and improving the performance of wireless radio frequency (RF) networks from a remote location. Their main tasks include monitoring network KPIs, troubleshooting interference or coverage issues, and implementing solutions to enhance signal quality and capacity. Working remotely, they use specialized software tools to access, analyze, and optimize cellular networks such as LTE, 5G, or Wi-Fi, ensuring reliable communication services for users.

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

To thrive as a Remote RF Optimization Engineer, you need a solid background in wireless communication principles, network optimization, and a degree in electrical or telecommunications engineering. Familiarity with RF planning tools (such as Atoll, Actix, or TEMS), drive test equipment, and certifications like CCNA or relevant vendor-specific credentials are highly valued. Strong analytical thinking, problem-solving abilities, and effective remote communication skills set top performers apart in this role. These skills ensure optimal network performance, efficient troubleshooting, and seamless collaboration on distributed engineering teams.

What are some common challenges faced by Remote RF Optimization Engineers, and how can they be addressed?

Remote RF Optimization Engineers often encounter challenges such as limited on-site access, coordinating with field teams, and troubleshooting network issues without direct physical observation. These challenges can be addressed by leveraging advanced remote monitoring tools, maintaining clear communication channels with local technicians, and utilizing simulation software to analyze and resolve signal problems. Building strong relationships with cross-functional teams and staying updated on the latest industry best practices also help in effectively managing remote optimization tasks.
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Remote Rf Optimization Engineer jobs near you
Distinguished AI/ML Engineering Lead

Distinguished AI/ML Engineering Lead

Frontier Technology

Huntsville, AL • Remote

$97K - $128K/yr

Other

Posted 9 days ago

Job description


Distinguished AI/ML Engineering Lead
ID
2026-7051
Category
Engineering
Type
Regular Full-Time
Location : Location
US-AL-Huntsville
Telecommute
Yes
Clearance Requirements
Secret
Overview

FTI Defense delivers mission-focused solutions to the Department of Defense and Intelligence Community 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.

FTI Defense is seeking a Distinguished AI/ML Engineer to serve as a technical leader, architect, and integrator - designing, building, deploying, and sustaining AI systems that transform complex mission data into trusted, explainable insights.

This is a hands-on builder role, not an analytics management position. The ideal candidate is equally comfortable writing model code, standing up ML pipelines, and integrating AI inference services into operational systems within secure environments. The right candidate blends deep AI/ML engineering expertise with system-level architecture leadership and an ability to unify data engineering, simulation modeling, and responsible AI principles into scalable, mission-ready capabilities.

Responsibilities
    Architect and integrate hybrid AI systems that combine traditional machine learning, deep learning, large language models (LLMs), and retrieval-augmented generation (RAG) pipelines.
  • Design and deploy scalable AI architectures including APIs, microservices, and model-serving frameworks that integrate seamlessly with analytic, simulation, or operational systems.
  • Lead the full AI/ML lifecycle - from data ingestion and feature engineering through training, deployment, and sustainment within secure DoD environments (IL5/IL6, ATO, GovCloud).
  • Engineer event-driven data pipelines and feature stores for both structured and unstructured data, including text, imagery, and simulation outputs.
  • Ensure Responsible AI practices by embedding traceability, explainability, and confidence scoring into deployed systems.
  • Implement and maintain MLOps pipelines (MLflow, Kubeflow, Airflow, Docker/Kubernetes) to support continuous integration, retraining, and drift detection.
  • Transition R&D prototypes into production, optimizing for mission constraints such as limited compute, edge environments, or disconnected operations.
  • Provide technical leadership and mentorship, setting standards for model quality, architectural design, and ethical AI deployment across programs.
  • Collaborate across engineering, data, and modeling teams to unify FTI's AI portfolio, ensuring interoperability and reuse across mission systems.
  • Support proposal and solution development, providing technical inputs for AI/ML architectures, data strategies, and Responsible AI assurance frameworks.
Education/Qualifications
  • Active Secret clearance required; TS/SCI strongly preferred.
  • Bachelor's degree in Computer Science, Engineering, or a related technical field (Master's or Ph.D. preferred).
  • 10+ years of overall experience in AI/ML development, with 5+ years designing and deploying scalable AI/ML architectures, including at least two full lifecycle implementations (from prototype to operational system).
  • Proficiency in Python, PyTorch, TensorFlow, and modern ML frameworks.
  • Experience designing or deploying systems using vector databases (Milvus, Pinecone, Weaviate), knowledge graphs, and semantic search frameworks.
  • Proven ability to design event-driven data pipelines using Databricks, Spark, Flink, or Kafka.
  • Demonstrated experience deploying AI/ML systems in secure, classified, or edge environments.
  • Familiarity with Responsible AI and assurance principles, including bias detection, explainability, human-machine teaming, and hallucination prevention.
  • Experience integrating AI models into simulation, modeling, or operational planning systems is highly desirable.
  • Experience transitioning R&D systems into accredited production environments.
  • Strong communication and mentoring skills, with the ability to lead technically while remaining deeply hands-on.

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