AI/ML Platform Engineer

Surge IT; Alexandria (VA); On-site; USD 120,000 - 150,000; Full time

Job summary

Surge IT is seeking a hands-on Senior AI/ML Platform Engineer located in Alexandria, Virginia, with over 10 years of IT experience. The ideal candidate will have a strong track record in building and operationalizing AI/ML systems across cloud environments, focusing on production-grade solutions.

The role requires deep skills in developing ML pipelines, using frameworks like TensorFlow and PyTorch, as well as hands-on experience with AWS, Kubernetes, and Terraform for scalable infrastructure. Candidates must have exceptional coding abilities in Python and Java.

Qualifications

• 10+ years of IT/engineering experience.
• 3+ years of hands-on AI/ML development experience.
• 4+ years working directly with AWS services.

Responsibilities

• Build and deploy production-grade ML/AI pipelines and services.
• Develop LLM-powered and NLP-driven applications.
• Write, optimize, and maintain high-quality Python-based ML code.
• Implement scalable infrastructure using Terraform, AWS, and Kubernetes.

Skills

Deep Learning frameworks: TensorFlow, PyTorch, Keras

LLMs, prompt engineering, NLP pipelines

Python and Java as primary languages

FastAPI and microservices for ML inference

Infrastructure as Code (Terraform)

Kubernetes and Docker for scalable ML workloads

Distributed/cloud systems design with AWS

Edge-to-cloud system integration experience

Job description

We are seeking a hands‑on Senior AI/ML Platform Engineer with 10+ years of IT experience and a strong track record of building, deploying, and operationalizing AI/ML systems. The ideal candidate is a doer who excels in implementing scalable, production‑grade AI/ML solutions across cloud environments.

Core Requirements

• 10+ years of IT/engineering experience
• 3+ years of hands‑on AI/ML development experience
• 4+ years working directly with AWS services (Lambda, EC2, S3, DynamoDB, IoT Core, API Gateway, Fargate/ECS)
• Proven experience deploying ML systems into production environments
• Strong coding skills and ability to build systems end‑to‑end

Key Skills

• Deep Learning frameworks: TensorFlow, PyTorch, Keras
• LLMs, prompt engineering, NLP pipelines
• Python and Java as primary languages; strong engineering fundamentals
• FastAPI and microservices for ML inference
• Infrastructure as Code (Terraform)
• Kubernetes and Docker for scalable ML workloads
• Distributed/cloud systems design with AWS
• Edge‑to‑cloud system integration experience
• Hands‑on build experience (not just design/architecture)

Responsibilities

• Build and deploy production‑grade ML/AI pipelines and services
• Develop LLM‑powered and NLP‑driven applications
• Write, optimize, and maintain high‑quality Python‑based ML code
• Implement scalable infrastructure using Terraform, AWS, and Kubernetes
• Build FastAPI‑based inference services and cloud APIs
• Collaborate with cross‑functional engineering teams to deliver high‑impact systems
• Troubleshoot, optimize, and own systems end‑to‑end as a hands‑on engineer

Preferred Skills

• Experience with distributed systems and microservices
• Strong understanding of ML model lifecycle, deployment patterns, and operational monitoring