The Associated Press is an independent global news organization dedicated to factual reporting. Founded in 1846, AP today remains the most trusted source of fast, accurate, unbiased news in all formats and the essential provider of the technology and services vital to the news business. More than half the world's population sees AP journalism every day.
Why this role matters:
The ML Engineer is a new role within the AP Engineering organization, responsible for shaping how we build and scale machine learning systems at AP, helping to lay the foundation for our machine learning capabilities. The ML Engineer has hands-on experience building and optimizing ML inference systems that run in production environments. This role will develop and tune pipelines that transform millions of photos, videos, and text documents into searchable representations using a combination of deep learning models (e.g., DistilBERT, SBERT, TransNetV2) and external multimodal APIs. The ideal candidate has experience optimizing inference at scale, orchestrating ML workloads, and working with both PyTorch and TensorFlow in a cloud environment, focusing on model performance, integration patterns, and inference efficiency.
This is an individual contributing role who will report directly to our Director of Development, Enterprise Application Services.
-
Design, build, and scale ML-powered inference systems that process large volumes of text, image, and video data to power news-based intelligence products.
-
-
TransNetV2 for video shot boundary detection at scale for archival video as well as real-time
-
SBERT for embedding generation from textual descriptions
-
External multimodal APIs for image/video captioning
-
Support hybrid search architectures by defining embedding/re-ranking interfaces, evaluation metrics, and inference performance requirements; partner with search/platform engineers on index configuration, sharding, and cluster tuning.
-
-
Cloud-based execution (e.g., AWS EC2, Batch, Lambda, SageMaker)
-
Optimize inference latency and throughput across distributed workloads using cloud-based resources (AWS EC2, Batch, Lambda, SageMaker, etc.)
-
Demonstrated ownership of deep-learning inference optimization in production (quantization, distillation, compilation, kernel/profile-level performance work) for transformer NLP and/or CV models.
-
Experience with both TensorFlow (SavedModel, tf.data, XLA, TFLite) and PyTorch (TorchScript, ONNX, FastAPI/TorchServe)
Who This Role is Not For:
Candidates whose primary background is MLOps platform work (e.g., DAG orchestration, Terraform, Kubernetes administration, generic CI/CD pipelines) will not be a fit. We are looking for a senior level engineer who has experience profiling a transformer, rewriting its serving path for a 2–3x latency reduction, tuning an HNSW index, and can tell us which SageMaker instance type will hit our p95 target at the lowest cost.
The anticipated salary range for this position is $145,000 - $180,000 based on a candidate’s skills, qualifications and location. The Associated Press offers comprehensive benefits, which include:
AP seeks to build an inclusive organization grounded in respect for differences. We support all aspects of diversity and provide equal employment opportunities to all employees and applicants without regard to race, color, religion, sex, marital status, national origin, age, sexual orientation, gender identity, disability, status as a veteran, or other characteristic protected by law.
