AI/ML Engineer
Overview
We are looking for an AI/ML Engineer to build, deploy, and maintain machine learning systems in production. This role bridges the gap between data science research and operational AI systems, focusing on scalable, reliable ML infrastructure.
Key Responsibilities
ML System Development
Build and deploy machine learning models into production environments
Develop MLOps pipelines for model training, validation, and deployment
Implement model monitoring, versioning, and automated retraining systems
Optimize model performance for real-time and batch inference scenarios
Infrastructure & Platform Engineering
Design and implement ML platforms and frameworks for data scientists
Build APIs and microservices for model serving and integration
Implement containerization and orchestration for ML workloads
Develop automated testing and validation frameworks for ML systems
AI System Integration
Integrate AI capabilities into existing enterprise applications
Implement LLM-based solutions and fine-tuning workflows
Build multi-agent AI systems and agentic frameworks
Develop edge AI solutions for real-time processing
Required Skills and Qualifications
Education & Experience
Bachelor's degree in Computer Science, Engineering, or related field
4+ years of experience in ML engineering or software development
2+ years of production ML system experience
Technical Skills
Programming: Expert Python, proficiency in Java, Go, or C++
ML Frameworks: TensorFlow, PyTorch, Scikit-learn, Hugging Face
MLOps: Kubeflow, MLflow, Airflow, Jenkins, GitLab CI/CD
Containerization: Docker, Kubernetes, container orchestration
Cloud Services: AWS SageMaker, Azure ML, GCP AI Platform
Preferred Qualifications
Experience with government or defense ML projects
Real-time ML inference optimization experience
Distributed computing and big data experience
LLM fine-tuning and deployment experience
Preferred Skills
What We Offer