AI Software Engineer

Job Description

About The Role

We’re looking for an AI/ML Software Engineer to play a foundational role in developing and deploying AI-powered solutions for our core product. You’ll work across the full AI/ML lifecycle—from defining and building models to evaluating and deploying large scale ML pipelines and real-time inference systems—while collaborating with cross-functional teams to deliver impactful, real-world AI applications.

What You’ll Do

• Build and Deploy AI/ML Models
  • Own and develop an AI model aligned with our core product needs within the first three months.
  • Validate AI-driven product features through real-world testing and feedback from warfighters.
  • Establish scalable MLOps pipelines and real-time inference services to streamline model training, deployment, runtime, and monitoring.
  • Own high model reliability and uptime by implementing monitoring across your work.
• Data Collection & Processing
  • Identify and integrate structured, unstructured, real-time, and batch data sources.
  • Work with internal logs, APIs, user interactions, and third-party datasets to improve model training quality.
• Continuous Improvement & Best Practices
  • Stay ahead of AI trends and emerging technologies to improve model performance.
  • Document and share best practices for AI/ML development.
  • Contribute to the hiring and mentoring of AI/ML talent as we grow our team.
  • Teach the wider team about the latest trends and significance in novel approaches in AI.

What We’re Looking For

• Strong Programming Skills
  • Expertise in at least one: Python, C++, or C.
• ML Framework Proficiency
  • Hands-on experience with AI/ML training and fine-tuning frameworks, including:
    • PyTorch, TensorFlow, CUDA, Jupyter Notebooks
    • Large Language Models (LLMs) and Open-Source Models (Llama, Anthropic, Mistral)
    • LangChain, Retrieval-Augmented Generation (RAG), Hugging Face, Exo Labs
• MLOps & Data Engineering Knowledge
  • Experience with data processing and pipeline frameworks such as Apache Kafka, Apache Airflow, AWS Kinesis, pandas, and dbt.
  • Understanding of AI model performance monitoring, data drift detection, and observability tools like Grafana or Kibana.
• AI Fundamentals & Security Awareness
  • Deep understanding of deep neural networks (DNNs), LLMs, over/underfitting, prompt engineering, and LLM security (jailbreaking risks and protections).
• Growth Mindset
  • Passion for continuous learning and staying current with the latest advancements in AI/ML, as well as teaching others

Are you interested in this position?

Apply by clicking on the “Apply Now” button below!

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