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Lila Sciences

Machine Learning Operations Engineer

Posted 24 Days Ago
Cambridge, MA
Mid level
Cambridge, MA
Mid level
The Machine Learning Operations Engineer will design data processing infrastructure, collaborate with researchers, and contribute to MLOps best practices, focusing on data management for machine learning applications.
The summary above was generated by AI

🚀 About Lila Sciences

Lila Sciences is the world’s first scientific superintelligence platform and autonomous lab for life, chemistry, and materials science.  We are pioneering a new age of boundless discovery by building the capabilities to apply AI to every aspect of the scientific method.  We are introducing scientific superintelligence to solve humankind's greatest challenges, enabling scientists to bring forth solutions in human health, climate, and sustainability at a pace and scale never experienced before. Learn more about this mission at  www.lila.ai    

At Lila, we are uniquely cross-functional and collaborative. We are actively reimagining the way teams work together and communicate. Therefore, we seek individuals with an inclusive mindset and a diversity of thought. Our teams thrive in unstructured and creative environments. All voices are heard because we know that experience comes in many forms, skills are transferable, and passion goes a long way.

If this sounds like an environment you’d love to work in, even if you only have some of the experience listed below, please apply.

🌟 Your Impact at Lila

We are seeking a mid-level Machine Learning Operations Engineer to join our growing team. In this role, you will focus on unifying data management at Lila by building and maintaining high performance and robust data pipelines to support a variety of machine learning use-cases. You will work closely with both LLM researchers and Applied AI Engineers to ensure the seamless integration of cutting-edge LLM research with scalable, production-ready systems for life science and physical science automation.

🛠️ What You'll Be Building

  • Design and implement high-performance data processing infrastructure for large language model training
  • Collaborate with researchers to implement novel data processing pipelines
  • Develop an easy-to-use, secure, and robust developer experience for researchers and engineers
  • Contribute to the MLOps best practices at Lila Sciences and write technical documentation for staff

🧰 What You’ll Need to Succeed

  • 3+ years of experience in software engineering, with a focus in data engineering or DevOps
  • Demonstrated experience deploying and maintaining machine learning models in production
  • Proficiency with Kubernetes, Docker, and Cloud (AWS Preferred)
  • Proficiency with CI/CD tools and Frameworks (GitHub Actions preferred)
  • Strong skills with Scripting languages (e.g. Python, Bash), VCS (git), and Linux
  • Proven experience in cross-functional teams and able to communicate effectively about technical and operational challenges.

✨ Bonus Points For

  • Proficiency with scalable data frameworks (Spark, Kafka, Flink)
  • Proven Expertise with Infrastructure as Code and Cloud best practices
  • Proficiency with monitoring and logging tools (e.g., Prometheus, Grafana)
  • Experience managing on-premises kubernetes environments (e.g. Rancher)

🌈 We’re All In

Lila Sciences is committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status.

🤝 A Note to Agencies

Lila Sciences does not accept unsolicited resumes from any source other than candidates. The submission of unsolicited resumes by recruitment or staffing agencies to Lila Sciences or its employees is strictly prohibited unless contacted directly by Lila Science’s internal Talent Acquisition team. Any resume submitted by an agency in the absence of a signed agreement will automatically become the property of Lila Sciences, and Lila Sciences will not owe any referral or other fees with respect thereto.

Top Skills

AWS
Bash
Docker
Flink
Github Actions
Grafana
Kafka
Kubernetes
Linux
Prometheus
Python
Spark

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