Contract: AI Operations Specialist

<p><strong>Why You'll Love This Role:&nbsp;</strong></p> <p>We're looking for an experienced Machine Learning Engineer to join the ML team at Newsela. This team works on projects ranging from classical Machine Learning to AI / Generative pipelines. &nbsp;This is a hands-on role. You'll work closely with ML/AI, data and site reliability engineers to take models from prototype to production, build robust data pipelines, and keep our services running smoothly as we continue to scale.</p> <p><strong>What You'll Be Doing:</strong></p> <ul> <li>Design and maintain CI/CD pipelines for ML model training, packaging, and deployment across our microservices.</li> <li>Manage containerized services on AWS ECS, optimizing for cost, latency, and availability.</li> <li>Automate infrastructure provisioning and service configuration with Terraform.</li> <li>Work to maintain and scale services that make use of third party LLM providers.</li> <li>Build and improve data pipelines that feed models from BigQuery, S3, and DynamoDB into training and inference workflows.</li> <li>Instrument services with observability tooling (Datadog, OpenTelemetry, Langfuse) and establish SLOs for model-serving endpoints.</li> <li>Collaborate with ML engineers to productionize new models using BentoML, FastAPI, and container-based serving.</li> </ul> <p><strong>About You:</strong></p> <ul> <li>2-3 years in ML Ops supporting ML/AI features, systems and workflows with 3-4 years prior experience in DevOps, CloudOps or SRE.</li> <li>Strong proficiency in Python.</li> <li>Hands-on experience with&nbsp;Docker containerization and container orchestration.</li> <li>Solid understanding of CI/CD for ML workflows in an enterprise production environment.</li> <li>Experience with Infrastructure as Code, preferably Terraform.</li> <li>Familiarity with cloud platforms — specifically AWS (ECS, ECR, S3, DynamoDB, CloudWatch) and GCP (BigQuery, Vertex AI).</li> <li>Experience with LLM integration and observability (OpenAI API, Google GenAI, Langfuse tracing).</li> <li>Experience building and maintaining data pipelines for ML training and feature engineering</li> <li>Familiarity with ML modeling workflows — training, evaluation, experiment tracking (e.g. MLFlow, Weights &amp; Biases), and model versioning</li> <li>Experience monitoring and flagging model drift over time.</li> <li>Exposure to NLP/NLU models and frameworks such as Hugging Face Transformers, spaCy, or sentence-transformers</li> <li>Knowledge of vector databases (LanceDB, FAISS) and embedding-based retrieval systems</li> <li>Experience with scaling and maintaining deep learning frameworks (TensorFlow, PyTorch) in production settings</li> <li>Familiarity with classical ML libraries (scikit-learn, XGBoost, LightGBM) and model explainability tools (SHAP)</li> <li>Working knowledge of ML serving frameworks such as BentoML or similar.</li> <li>Comfort working with FastAPI or similar async Python web frameworks.</li> </ul> <p>Please note that given the nature of the contract, this role will not be eligible to participate in company-sponsored benefits</p> <h3><span style="font-size: 10pt;"><strong>About Newsela:</strong></span></h3> <p>Newsela is a leading education technology company dedicated to meaningful classroom learning for every student. We deliver integrated, AI-powered solutions designed to unlock student engagement, empower teachers, and drive meaningful learning outcomes. Our suite of products supports knowledge and skill development, writing practice, daily instruction, assessment, and data-informed decision-making across K–12 classrooms. Grounded in learning science research, Newsela’s solutions integrate content, assessment, and analytics to help educators track progress, understand student outcomes, and deliver high-impact instruction that supports every learner.</p> <p><span style="font-size: 10pt;">#LI-Remote</span></p>