Company Name: Solace (solace.health)

Job Details: Hiring Remotely in United States Remote Mid level

Job Url: https://builtin.com/job/python-machine-learning-engineer/6458645

Job Description: Solace is a healthcare advocacy marketplace that connects patients and families to experts who help them understand and take charge of their personal healthAbout the RoleAs a Python ML Engineer at Solace, you’ll own the deployment and operationalization of machine learning models that power intelligent features across our platform. You’ll work hand-in-hand with data scientists and product teams to take algorithms from prototype to production—building scalable, reliable systems in AWS that directly improve healthcare access and outcomes for our patients.You are a builder at heart—someone who can navigate between code, infrastructure, and real-world impact. You understand the ML lifecycle end-to-end and thrive on making advanced analytics deployable, observable, and maintainable. Whether you're deploying models with SageMaker, building inference APIs with FastAPI, or automating pipelines with Airflow, you’re driven by shipping practical solutions that matter.About SolaceHealthcare in the U.S. is fundamentally broken. The system is so complex that 88% of U.S. adults do not have the health literacy necessary to navigate it without help. Solace cuts through the red tape by pairing patients with expert advocates and giving them tools to make better decisions—and get better outcomes.We're a Series B startup, founded in 2022 and backed by Inspired Capital, Craft Ventures, Menlo Ventures, Torch Capital, and Signalfire. Our fully remote U.S. team is lean, mission-driven, and growing fast.Solace isn’t a place to coast. We’re here to fix healthcare—and that takes urgency, precision, and heart. If you're ready to stretch your skills, ship impactful ML infrastructure, and collaborate with a high-performance team, you're in the right place.Read more in our Wall Street Journal funding announcement hereWhat You’ll DoDeploy machine learning models from prototype to production, working closely with data scientists and product stakeholdersBuild scalable ML inference systems using AWS services like SageMaker, Lambda, ECS, and S3Develop APIs and serverless endpoints to enable real-time and batch inferenceDesign and automate pipelines for data prep, feature engineering, training, and retraining workflows using Airflow or Step FunctionsMonitor and optimize model performance, observability, and reliabilityChampion best practices around MLOps, CI/CD, and reproducibilityImprove model latency, cost, and performance in production environmentsContribute to the evolution of Solace’s ML infrastructure and internal toolingWhat You Bring to the TableStrong Python engineering skills, especially in ML model deploymentProven experience with AWS services including SageMaker, Lambda, ECS, and API GatewayComfort building APIs with FastAPI or Flask for model inferenceFamiliarity with orchestration tools like Airflow and Step FunctionsUnderstanding of CI/CD, containerization (Docker), and versioning for MLSolid SQL skills and experience integrating with Snowflake or PostgresBonus: experience with ML observability tools (e.g. MLflow), serverless architectures, or startup/healthcare settingsOur Tech StackPythonAWS (SageMaker, Lambda, S3, ECS, Step Functions, API Gateway)AirflowFastAPI / FlaskDockerPostgres / SnowflakeStreamlit / DashThis is a remote position. Applicants must be based in the United States.Up for the Challenge? We look forward to meeting you.Fraudulent Recruitment Advisory: Solace Health will NEVER request bank details or offer employment without an interview. All legitimate communications come from official solace.health emails only or ashbyhq.com. Report suspicious activity to hiring@solace.health.