Senior Machine Learning Engineer

Location: San Francisco Bay, south Bay in office/hyrid

Join a forward-thinking company dedicated to transforming healthcare using AI. Our goal is to leverage every patient's journey to inform healthcare decisions, enhancing treatment plans and facilitating novel drug discoveries. By analyzing extensive patient health data, we aim to provide timely and accurate care. If you're passionate about improving healthcare through technological innovation, we invite you to contribute to shaping the future with us.

 

Role Overview

In the role of Machine Learning Engineer, you'll play a crucial part in our data team, tasked with the creation, execution, and upkeep of ML pipelines and services. Your main responsibilities will include developing and refining ML training and inference processes, ensuring their availability and efficiency to boost AI productivity and reduce cycle times. Collaborating closely with a diverse team of professionals, you'll support data-centric decision-making and enhance business intelligence.

 

Key Responsibilities

- Design, build, and implement ML models into operational environments.

- Develop dependable ML training and inference systems utilizing MLFlow and Kubeflow.

- Collaborate with the data science team to scale their algorithms effectively.

- Guarantee the performance, quality, and responsiveness of the models.

- Work with various teams to define, design, and introduce new features.

- Continuously explore, assess, and integrate new technologies to optimize development processes.

 

Qualifications

- A Bachelor’s degree in a technical field such as Computer Science or Engineering, with a preference for advanced degrees.

- At least 5 years of relevant experience in creating ML training and inference frameworks with tools like MLFlow and Kubeflow, particularly in a cloud computing environment.

- Profound knowledge of ML frameworks, libraries, data structures, data modeling, and software design.

- Proficiency in a major programming language (e.g., Python).

- Practical experience with a range of ML algorithms, tools, and platforms.

- Familiarity with cloud computing services.

- Strong problem-solving capabilities and teamwork skills.

 

Additional Skills (Preferred but Not Mandatory)

- Understanding of data streaming technologies.

- Background in ELT and ETL processes for feature engineering.

- Experience with data visualization tools.

- Certifications in relevant technological tools and platforms.

In this role, you will significantly influence our data infrastructure's development and ensure the data's availability and reliability for analysis. Your contributions will be pivotal to our organization's data-driven strategies and overall achievements.

 

Key Areas of Interest

- Machine Learning, Model Optimization, Hyperparameter Adjustment, Deep Learning, Large-Scale Language Models, Implementation, ML Infrastructure, Resource Management, Cloud-Neutral Practices, MLOps, Continuous Processes, DevOps Tools, Cloud Computing Platforms, Data Science, System Scalability, ML Frameworks, Inference Systems, Data Engineering Practices