Senior Machine Learning Engineer

About the Opportunity Our client, a globally recognized media and information organization, is building a next-generation intelligence and data products platform leveraging large-scale machine learning systems across text, image, and video content. This team is focused on creating enterprise intelligence products powered by semantic search, embeddings, multimodal AI pipelines, and large-scale inference systems. The environment is highly technical, builder-oriented, and operates with startup energy inside a well-established organization. This is a hands-on ML Systems Engineering role focused on production-scale inference optimization and ML infrastructure — not pure research or model development. What You’ll Be Doing • Design, build, and optimize large-scale ML inference systems for text, image, and video workloads • Scale semantic/vector search and embedding pipelines across millions of media assets • Optimize inference latency, throughput, and cost efficiency for production ML systems • Work with transformer-based NLP and computer vision models in production environments • Improve and operationalize multimodal AI pipelines using existing/open-source models • Build scalable data processing systems across CPU/GPU cloud infrastructure • Partner closely with Data Science and Platform teams to productionize ML workflows • Contribute to hybrid search and retrieval systems using vector search and reranking approaches • Monitor and improve performance, reliability, and efficiency across distributed ML workloads Required Qualifications • 8+ years of experience building production ML systems • Strong experience optimizing ML inference performance in production • Hands-on experience with: • PyTorch • TensorFlow • ONNX / TorchScript • Transformer-based NLP models • Experience building or supporting semantic/vector search systems • Experience deploying ML systems in AWS cloud environments • Strong understanding of distributed processing and scalable ML pipelines • Experience with multimodal workloads involving text, image, or video processing • Familiarity with embedding generation and retrieval systems Strongly Preferred • Video processing experience (highly preferred) • Experience with large-scale inference optimization • Familiarity with reranking systems and hybrid search architectures • Experience with HuggingFace models and modern ML tooling • Experience optimizing GPU-based workloads • Familiarity with multimodal AI APIs and services What This Role Is • Production ML Systems Engineering • Inference Optimization • Semantic Search & Embeddings • Distributed ML Infrastructure • Scalable AI Pipeline Engineering What This Role Is Not • Pure Data Science • Research-Focused AI • Greenfield Model Architecture Design • Traditional MLOps/DevOps Ownership Additional Details • Fully remote • Preference for East Coast collaboration hours • 6-month contract-to-hire • US Citizens and Green Card holders only Applicants must be legally authorized to work in the United States and must not require employer sponsorship now or in the future.