Find & Apply For Artificial Intelligence Engineer Jobs in Horsham, Pennsylvania

Role:

AI / ML OPS

Engineer Location:

Horsham, PA. Remote allowed (Eastern Time Zone)

Duration:

7

Months Role:

AI / ML OPS

Engineer We are seeking an AI Developer to design, build, and productionize end-to-end AI solutions across LLMs, RAG pipelines, model fine-tuning, and cloud deployment. This role will work closely with product, engineering, and data teams to build scalable AI features that are reliable, performant, and secure in production environments. Responsibilities

• Design and implement end-to-end AI features, including RAG systems, agent workflows, embeddings pipelines, and fine-tuned LLM applications
• Build and maintain data ingestion, chunking, embedding, retrieval, and prompt orchestration pipelines
• Fine-tune and evaluate open-source and proprietary LLMs using techniques such as LoRA, QLoRA, PEFT, and supervised fine-tuning
• Deploy and serve custom LLMs in Azure environments using Azure Machine Learning, AKS, Container Apps, or related services
• Optimize inference performance using quantization, batching, model parallelism, and GPU-aware serving strategies
• Work with model formats such as Safetensors, GGUF, ONNX, and TensorRT for efficient loading, portability, and deployment
• Build scalable APIs and services for LLM inference, streaming responses, and model orchestration
• Implement model monitoring, logging, evaluation, prompt testing, and feedback loops
• Collaborate with product managers and stakeholders to translate business requirements into AI capabilities
• Explain technical trade-offs clearly to non-technical audiences, including model size, quantization, latency, cost, and accuracy

AI Skills:

All contractor resources are expected to demonstrate baseline proficiency in enterprise-approved AI tools as part of their day-to-day responsibilities. This includes, but is not limited to: o

Consistent Use:

Maintain a minimum of 90% weekly usage of AI tools such as GitHub Copilot, Microsoft 365 Copilot, and other GenAI platforms approved by the enterprise. o

Applied Productivity:

Leverage AI tools to enhance coding, documentation, data analysis, and decision-making workflows. o

Continuous Learning:

Stay current with evolving AI capabilities and features and apply them to improve delivery quality and velocity.