在罗氏，我们鼓励每位同事展现真实的自己；我们欣赏独特且出众的品质。罗氏的文化鼓励积极的表达、开放的对话和真诚的连结，在这里，你将因为做自己而被重视、接纳和尊重，并得到个人的提升和职业的发展。所有的这一切，都是为了更好地预防、阻止和治愈疾病，并确保医疗资源的可及性和可持续性。欢迎加入罗氏，一个重视每种声音的地方。
职位
As a Senior Data Scientist - ML Engineering, you will join the Global Analytics and Technology Center of Excellence (GATE) in San José, Costa Rica. In this role, you will own the end-to-end path from machine learning models to scalable, reliable production systems supporting global Roche affiliates. Operating across the full MLOps and software engineering stack, you will architect cloud-native ML pipelines, build automated testing and CI/CD frameworks, instrument model observability, and set high software craftsmanship standards across the engineering team.
The Opportunity
ML Systems & Platform Engineering: Architect, deploy, and maintain end-to-end production ML services, training pipelines, containerization, and orchestration (Airflow/Dagster) with strict SLAs for performance and cost.
MLOps Capability Building: Design reusable MLOps platform components including feature stores, model registries, experiment tracking, and automated CI/CD deployment pipelines using GitLab CI or GitHub Actions.
Model Accuracy & Observability: Build automated back-testing frameworks and instrumentation for tracking data/concept drift, feature anomalies, and model performance decay, translating diagnostic findings into root-cause fixes.
Cloud & Pipeline Automation: Implement cloud-native ML infrastructure across AWS, Azure, or GCP, systematically automating manual tasks and maintaining data synchronization contracts.
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Technical Leadership & Coaching: Establish engineering standards through code reviews, refactoring research code, and mentoring data scientists on production-grade software practices.
Stakeholder Support: Partner with global affiliate teams to explain predictive model outputs, address business needs, and incorporate feedback into technical roadmaps.
Who You Are
Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, Statistics, or a quantitative discipline.
7+ years of relevant experience running and maintaining machine learning systems in production environments.
Deep proficiency in Python, Linux/Bash, SQL, modern pipeline tools (Spark, dbt, Snowflake, Databricks), and clean API design.
Hands-on expertise with containerization (Docker, Kubernetes), MLOps tools (MLflow, Weights & Biases), orchestration (Airflow), and CI/CD automation.
Proven experience in cloud architectures (AWS, Azure, or GCP) and core ML frameworks (scikit-learn, XGBoost, PyTorch, TensorFlow, time-series forecasting).
Strong analytical mindset focused on quality control, data contracts, and system observability (experience with LLMOps, streaming/Kafka, or GPU workloads is a plus).
Must be currently based in Costa Rica or hold valid work authorization for San José.
No relocation benefits are offered for this position.
我们是谁
打造更健康的未来是促使我们创新的动力。全球超过100,000名员工共同致力于推进科学，确保今天和明天的人们，都能获得高质量的医疗资源。我们的努力帮助了2600多万人使用我们的药物进行治疗，我们的诊断产品运行超过300亿次检测。罗氏通过赋能探索新的可能、激发创造力并保持高标准以提供突破传统的医疗解决方案，对全球的医疗环境带去推动和影响。
让我们一起，构建更健康的未来。
罗氏提供平等的职业发展机会。
