[Remote] Machine Learning Operations Engineer

Note: The job is a remote job and is open to candidates in USA. The Associated Press is an independent global news organization dedicated to factual reporting. The Machine Learning Operations Engineer will own the production lifecycle of machine-learning systems, ensuring reliable, secure, and cost-effective operation of ML workloads in production environments.ResponsibilitiesDesign, deploy, and operate end‑to‑end production ML pipelines across Dev, QA, and Prod environmentsSet up and manage AWS SageMaker pipelines, endpoints, and monitoring for large scale inference workloads, including embedding generation, named entity recognition, reranking, and video processingOwn GPU and CPU infrastructure selection, scaling, and optimization, including instance benchmarking, autoscaling behavior, and load testingDeploy, monitor, and operate inference services that support hundreds of thousands of queries per day across text, image, and video pipelinesEstablish standardized ML deployment patterns at AP, including containerization and orchestration strategies, environment isolation (Dev / QA / Prod) and versioned promotion, rollback, and recovery mechanismsImplement monitoring, alerting, drift detection, and evaluation metrics for production ML systems, tracking latency, error rates, throughput, and model/data driftEnable A/B testing and controlled rollout strategies for ML models in production, in partnership with engineering and product teamsPartner closely with ML Engineers, Data Scientists, DevOps, and Platform teams to operationalize new models and pipeline improvements, promote systems across environments safely, and ensure deployments meet reliability, scale, and cost targetsManage high-throughput I/O and data movement for large collections of media assets (text, images, video), avoiding CPU, network, and storage bottlenecksReduce operational risk by enforcing reproducibility, observability, security, and cost controls across all production ML systemsSkills5+ years of experience deploying and operating ML inference systems in productionStrong experience with AWS SageMaker, including pipelines, endpoints, monitoring, and multi‑environment deploymentsExpertise deploying ML models using PyTorch and TensorFlow from an operational and serving perspectiveProven experience with model deployment and orchestration, including containerized inference and autoscalingExperience selecting, evaluating, and optimizing compute resources (GPU/CPU) for production ML workloadsExperience setting up monitoring, evaluation metrics, and A/B testing frameworks for ML systems in productionAbility to collaborate effectively with ML Engineers, Data Scientists, and platform teams in a shared ownership modelOperational experience supporting ML systems involving transformer‑based NLP models (e.g., BERT‑family models), computer vision models, and ranking and reranking systemsFamiliarity operating systems that use common ML model types such as convolutional and feed‑forward neural networks, ranking algorithms, and approximate Nearest Neighbor methods (e.g., HNSW)Experience running ML workloads over large‑scale text, image, and video datasetsBenefitsCompetitive medical, dental and vision coverageRetirement benefitsCompany paid life insurancePaid vacation and sick daysPaid parental leave for any new parentMental well-being resourcesCompany OverviewThe Associated Press is a source of independent newsgathering, supplying a steady stream of news to its members, and more. It was founded in 1846, and is headquartered in New York, New York, USA, with a workforce of 1001-5000 employees. Its website is http://www.ap.org.Company H1B SponsorshipThe Associated Press has a track record of offering H1B sponsorships, with 1 in 2026, 2 in 2025, 7 in 2024, 4 in 2023, 4 in 2022, 2 in 2021, 2 in 2020. Please note that this does not guarantee sponsorship for this specific role.