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Remote Google Machine Learning Engineer Jobs in Alabama

This position is remote, but you MUST be located in our business footprint, which includes the ... Knowledge of artificial intelligence and machine learning. * Understanding of workflow-based logic.

This position is remote, but you MUST be located in our business footprint, which includes the ... Knowledge of artificial intelligence and machine learning. * Understanding of workflow-based logic.

This position is remote, but you MUST be located in our business footprint, which includes the ... Knowledge of artificial intelligence and machine learning. * Understanding of workflow-based logic.

This position is remote, but you MUST be located in our business footprint, which includes the ... Knowledge of artificial intelligence and machine learning. * Understanding of workflow-based logic.

This position is remote, but you MUST be located in our business footprint, which includes the ... Knowledge of artificial intelligence and machine learning. * Understanding of workflow-based logic.

$171K - $210K/yr

Data Engineering, Data Science or Machine Learning * Operations, Security and Data Governance ... Employee Resource Groups EEO/VEVRAA #LI-MH2 #LI-Remote

AI Solution Engineer- Ops

Huntsville, AL ยท On-site +1

$121K - $169K/yr

... days remote Position Description This position supports the Golden Dome Supply Chain Enterprise ... machine learning model operations within the operations and implementation branch. The engineer ...

AI Solution Engineer- Ops

Huntsville, AL ยท On-site +1

$121K - $169K/yr

... days remote Position Description This position supports the Golden Dome Supply Chain Enterprise ... machine learning model operations within the operations and implementation branch. The engineer ...

This is a role for engineers who enjoy asking "why," digging into complex problems, and continuously learning. This remote role welcomes candidates anywhere in the US. Preference will be given to ...

Data Science Tutor

Montgomery, AL ยท Remote

$18 - $40/hr

Deep knowledge of statistical analysis, data wrangling, exploratory data analysis, machine learning, data visualization, SQL, Python or R programming, hypothesis testing, and communication of data ...

Data Science Tutor

Huntsville, AL ยท Remote

$18 - $40/hr

Deep knowledge of statistical analysis, data wrangling, exploratory data analysis, machine learning, data visualization, SQL, Python or R programming, hypothesis testing, and communication of data ...

Data Science Tutor

Birmingham, AL ยท Remote

$18 - $40/hr

Deep knowledge of statistical analysis, data wrangling, exploratory data analysis, machine learning, data visualization, SQL, Python or R programming, hypothesis testing, and communication of data ...

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Remote Google Machine Learning Engineer information

What is a Remote Google Machine Learning Engineer?

A Remote Google Machine Learning Engineer is a professional who designs, builds, and deploys machine learning models and artificial intelligence solutions, often using Google Cloud technologies, while working from a remote location. These engineers collaborate with cross-functional teams to solve complex business problems, optimize data pipelines, and improve model performance. Their responsibilities typically include data preprocessing, model selection, training, evaluation, and deployment, all while ensuring scalability and security. Working remotely allows them to contribute to projects from anywhere, leveraging cloud-based tools and collaboration platforms.

What are the key skills and qualifications needed to thrive as a Remote Google Machine Learning Engineer, and why are they important?

To thrive as a Remote Google Machine Learning Engineer, you need a strong background in computer science, mathematics, and machine learning algorithms, typically supported by a relevant degree and experience in building scalable models. Proficiency with tools such as TensorFlow, Python, Google Cloud Platform (GCP), and familiarity with distributed systems is essential. Excellent problem-solving, communication, and self-management skills are crucial for effective remote collaboration and innovation. These capabilities enable engineers to deliver impactful machine learning solutions while seamlessly integrating with global Google teams.

How do Remote Google Machine Learning Engineers typically collaborate with cross-functional teams while working from different locations?

Remote Google Machine Learning Engineers often use a combination of video conferencing, cloud-based collaboration tools, and shared code repositories to work closely with data scientists, product managers, and software engineers. Regular stand-up meetings, sprint planning sessions, and detailed documentation help ensure everyone is aligned and project milestones are met. Despite being remote, engineers are encouraged to proactively communicate progress, share insights, and participate in code reviews to maintain a strong team dynamic and drive successful project outcomes.
What are the most commonly searched types of Google Machine Learning Engineer jobs in Alabama? The most popular types of Google Machine Learning Engineer jobs in Alabama are:
What are popular job titles related to Remote Google Machine Learning Engineer jobs in Alabama? For Remote Google Machine Learning Engineer jobs in Alabama, the most frequently searched job titles are:
What job categories do people searching Remote Google Machine Learning Engineer jobs in Alabama look for? The top searched job categories for Remote Google Machine Learning Engineer jobs in Alabama are:
What cities in Alabama are hiring for Remote Google Machine Learning Engineer jobs? Cities in Alabama with the most Remote Google Machine Learning Engineer job openings:
AI/ML Engineer

AI/ML Engineer

Frontier Technology Inc.

Huntsville, AL โ€ข Remote

Full-time

Re-posted 25 days ago


Job description

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.


  • 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.

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.
  • Bachelorโ€™s or Masterโ€™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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