Senior Data Scientist - ML Engineering & MLOps

Posted 12 Days Ago
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San José, San José, CRI
In-Office
Senior level
Healthtech • Biotech • Pharmaceutical
The Role
Owns the end-to-end development and operation of production machine learning systems. Responsibilities include architecting cloud-native ML pipelines, building MLOps components, automating CI/CD, implementing model testing and observability, monitoring drift and performance, and maintaining scalable infrastructure. The role also establishes engineering standards, mentors data scientists, and partners with global teams to deliver reliable predictive solutions.
Summary Generated by Built In

At Roche you can show up as yourself, embraced for the unique qualities you bring. Our culture encourages personal expression, open dialogue, and genuine connections,  where you are valued, accepted and respected for who you are, allowing you to thrive both personally and professionally. This is how we aim to prevent, stop and cure diseases and ensure everyone has access to healthcare today and for generations to come. Join Roche, where every voice matters.

The Position

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.
  • 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.

 

 

Who we are

A healthier future drives us to innovate. Together, more than 100’000 employees across the globe are dedicated to advance science, ensuring everyone has access to healthcare today and for generations to come. Our efforts result in more than 26 million people treated with our medicines and over 30 billion tests conducted using our Diagnostics products. We empower each other to explore new possibilities, foster creativity, and keep our ambitions high, so we can deliver life-changing healthcare solutions that make a global impact.


Let’s build a healthier future, together.

Roche is an Equal Opportunity Employer.

Skills Required

  • 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
  • Proficiency in Python, Linux/Bash, SQL, Spark, dbt, Snowflake, and Databricks
  • Experience with clean API design
  • Hands-on experience with Docker and Kubernetes
  • Hands-on experience with MLflow, Weights & Biases, and Airflow
  • Experience with CI/CD automation
  • Experience with AWS, Azure, or GCP cloud architectures
  • Experience with scikit-learn, XGBoost, PyTorch, TensorFlow, and time-series forecasting
  • Experience with quality control, data contracts, and system observability
  • Currently based in Costa Rica or holding valid work authorization for San Jose
  • Experience with LLMOps, streaming/Kafka, or GPU workloads

Roche Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Roche and has not been reviewed or approved by Roche.

  • Retirement Support — U.S. materials describe a 401(k) with both matching and an additional company contribution, supported by formal plan documents and true‑up features. This structure is positioned as a standout element of the total package, particularly at Genentech.
  • Leave & Time Off Breadth — Time‑off provisions include substantial vacation, a year‑end shutdown, and a paid six‑week sabbatical after six years. These elements indicate a recharge‑oriented approach within the U.S. offering.
  • Healthcare Strength — Company materials emphasize comprehensive medical, dental, vision, and mental‑health resources alongside well‑being programs. Benefits pages consistently highlight breadth across core health coverage elements.

Roche Insights

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The Company
Provincia de Buenos Aires
93,797 Employees
Year Founded: 1896

What We Do

Roche is a global pioneer in pharmaceuticals and diagnostics focused on advancing science to improve people’s lives. The combined strengths of pharmaceuticals and diagnostics under one roof have made Roche the leader in personalised healthcare – a strategy that aims to fit the right treatment to each patient in the best way possible. Roche is the world’s largest biotech company, with truly differentiated medicines in oncology, immunology, infectious diseases, ophthalmology and diseases of the central nervous system. Roche is also the world leader in in vitro diagnostics and tissue-based cancer diagnostics, and a frontrunner in diabetes management. Founded in 1896, Roche continues to search for better ways to prevent, diagnose and treat diseases and make a sustainable contribution to society. The company also aims to improve patient access to medical innovations by working with all relevant stakeholders. Thirty medicines developed by Roche are included in the World Health Organization Model Lists of Essential Medicines, among them life-saving antibiotics, antimalarials and cancer medicines. Roche has been recognised as the Group Leader in sustainability within the Pharmaceuticals, Biotechnology & Life Sciences Industry ten years in a row by the Dow Jones Sustainability Indices (DJSI).

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