At a Glance
- Tasks: Join us as a Machine Learning Operations Engineer to build and maintain data pipelines for AI applications.
- Company: Lila Sciences is an innovative tech company transforming science with AI, backed by Flagship Pioneering.
- Benefits: Enjoy flexible remote work options and access to cutting-edge technology in AI and automation.
- Why this job: Be part of a mission-driven team that values creativity, collaboration, and diverse perspectives.
- Qualifications: 3+ years in software engineering, focusing on data engineering or DevOps, with strong skills in cloud technologies.
- Other info: We encourage applicants with varied experiences; passion and potential matter most!
The predicted salary is between 36000 - 60000 ÂŁ per year.
Lila Sciences is a privately held, early-stage technology company pioneering the application of artificial intelligence to transform every aspect of the scientific method. Lila is backed by Flagship Pioneering, which brings the courage, long-term vision, and resources needed to realize unreasonable results. Join our mission-driven team and contribute to the future of science.
Our Life Sciences effort is leveraging AI and high-throughput automation for valuable therapeutic discovery and development across biological modalities. And our Physical Sciences effort is developing a novel AI and data-driven approach to materials discovery and development to accelerate the transition to a sustainable economy.
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.
The Role
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.
Responsibilities:
- 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
Qualifications:
- 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.
Preferred Qualifications:
- 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)
Working at Lila Sciences, you would have access to advanced technology in the areas of:
- AI experimental design and simulation
- Automated liquid handling and instrumentation
Location:
Cambridge, MA preferred; open to remote.
More About Flagship Pioneering
Flagship Pioneering is a biotechnology company that invents and builds platform companies, each with the potential for multiple products that transform human health or sustainability. Since its launch in 2000, Flagship has originated and fostered more than 100 scientific ventures, resulting in more than $90 billion in aggregate value. Many of the companies Flagship has founded have addressed humanity’s most urgent challenges: vaccinating billions of people against COVID-19, curing intractable diseases, improving human health, preempting illness, and feeding the world by improving the resiliency and sustainability of agriculture.
Flagship has been recognized twice on FORTUNE’s “Change the World” list, an annual ranking of companies that have made a positive social and environmental impact through activities that are part of their core business strategies, and has been twice named to Fast Company’s annual list of the World’s Most Innovative Companies. Learn more about Flagship at .
Flagship Pioneering and our ecosystem companies are 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.
At Flagship, we recognize there is no perfect candidate. If you have some of the experience listed above but not all, please apply anyway. Experience comes in many forms, skills are transferable, and passion goes a long way. We are dedicated to building diverse and inclusive teams and look forward to learning more about your unique background.
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Lila Sciences, Inc. | Cambridge, MA Machine Learning Operations Engineer employer: Flagship Pioneering
Contact Detail:
Flagship Pioneering Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Lila Sciences, Inc. | Cambridge, MA Machine Learning Operations Engineer
✨Tip Number 1
Familiarize yourself with the specific technologies mentioned in the job description, such as Kubernetes, Docker, and AWS. Having hands-on experience or projects that showcase your skills with these tools can set you apart during the interview process.
✨Tip Number 2
Highlight any collaborative projects you've worked on, especially those involving cross-functional teams. Lila Sciences values teamwork and communication, so demonstrating your ability to work well with others will be crucial.
✨Tip Number 3
Prepare to discuss your experience with MLOps best practices and how you've implemented them in previous roles. Being able to articulate your approach to maintaining machine learning models in production will show your readiness for this position.
✨Tip Number 4
Research Lila Sciences and Flagship Pioneering to understand their mission and values. Tailoring your conversation to align with their focus on innovation and sustainability can demonstrate your genuine interest in joining their team.
We think you need these skills to ace Lila Sciences, Inc. | Cambridge, MA Machine Learning Operations Engineer
Some tips for your application 🫡
Understand the Company Culture: Familiarize yourself with Lila Sciences' mission and values. Highlight your alignment with their focus on collaboration, inclusivity, and innovation in your application.
Tailor Your Resume: Customize your resume to emphasize relevant experience in machine learning operations, data engineering, and DevOps. Be sure to include specific projects or achievements that demonstrate your skills with tools like Kubernetes, Docker, and AWS.
Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for AI and its applications in life sciences. Discuss how your background and experiences make you a great fit for the role and the company’s mission.
Showcase Your Technical Skills: In your application, clearly outline your proficiency with CI/CD tools, scripting languages, and scalable data frameworks. Provide examples of how you've successfully deployed machine learning models in production environments.
How to prepare for a job interview at Flagship Pioneering
✨Show Your Passion for AI and Science
Lila Sciences is all about transforming the scientific method with AI. Make sure to express your enthusiasm for both artificial intelligence and the life sciences during the interview. Share any relevant projects or experiences that highlight your passion and how you envision contributing to their mission.
✨Demonstrate Your Technical Skills
Be prepared to discuss your experience with data engineering, machine learning models, and tools like Kubernetes, Docker, and AWS. Bring examples of past projects where you've successfully deployed and maintained ML models in production, as this will showcase your technical expertise.
✨Emphasize Collaboration and Communication
Since Lila values cross-functional teamwork, highlight your ability to work collaboratively with researchers and engineers. Share specific instances where you've effectively communicated technical challenges and solutions within a team setting, demonstrating your inclusive mindset.
✨Prepare for Unstructured Problem-Solving
Lila thrives in creative environments, so be ready to tackle open-ended questions or scenarios during the interview. Think about how you approach problem-solving in unstructured situations and be prepared to discuss your thought process and any innovative solutions you've implemented in the past.