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Remote Tensorflow Developer Jobs in Alabama (NOW HIRING)

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Remote Tensorflow Developer information

What is a Remote Tensorflow Developer job?

A Remote TensorFlow Developer job involves designing, implementing, and optimizing machine learning models using TensorFlow while working from a remote location. Developers in this role typically collaborate with data scientists, engineers, and product teams to build AI-driven applications and improve model performance. Responsibilities may include data preprocessing, model training, deployment, and fine-tuning for scalability and efficiency. Strong knowledge of deep learning, neural networks, and cloud platforms is often required.

What are the key skills and qualifications needed to thrive in the Remote Tensorflow Developer position, and why are they important?

To thrive as a Remote Tensorflow Developer, you need deep knowledge of machine learning concepts, strong proficiency in Python programming, and hands-on experience with Tensorflow framework. Experience with cloud platforms (such as AWS, GCP, or Azure), model deployment, and relevant Tensorflow Developer certification are highly valuable. Excellent problem-solving abilities, self-motivation, and effective remote communication skills help developers stand out. These qualities are crucial for building robust machine learning solutions, efficiently collaborating with distributed teams, and delivering high-impact results in a remote setting.

What are some typical challenges faced by Remote Tensorflow Developers, and how are these addressed?

Remote Tensorflow Developers often face challenges such as collaborating across different time zones, managing large datasets, and keeping up with rapidly changing machine learning technologies. These challenges are typically addressed through robust communication tools (like Slack or Zoom), using version control systems for code collaboration, and adopting efficient cloud-based workflows for data and model sharing. Teams may also conduct regular virtual stand-ups and knowledge-sharing sessions to stay aligned on projects and share learnings. Engaging in continuous learning and attending online workshops or conferences also helps remote developers stay updated and effective in their roles.

What are popular job titles related to Remote Tensorflow Developer jobs in Alabama? For Remote Tensorflow Developer jobs in Alabama, the most frequently searched job titles are:
What job categories do people searching Remote Tensorflow Developer jobs in Alabama look for? The top searched job categories for Remote Tensorflow Developer jobs in Alabama are:
What cities in Alabama are hiring for Remote Tensorflow Developer jobs? Cities in Alabama with the most Remote Tensorflow Developer job openings:
Remote Tensorflow Developer jobs near you
AI/ML Engineer

AI/ML Engineer

Frontier Technology Inc.

Huntsville, AL • On-site, Remote

Full-time

Posted 8 hours 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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