Senior Applied Scientist, Amazon CloudWatch Logs

Amazon CloudWatch is the native AWS monitoring and observability service for cloud resources and applications. We are seeking a talented Senior Applied Scientist to develop next-generation scientific methods and infrastructure to support a core AWS business that delivers critical services to millions of customers operating at scale.

This is a high visibility and high impact role that work on highly strategic projects in the AI / ML and Analytics space, will interact with all levels of AWS leadership.

We are developing solutions that not only surface the what but also the why and how to fix it , without requiring operators to have extensive domain knowledge and technical expertise to efficiently troubleshoot and remediate incidents.

Using decades of AWS operational excellence coupled with the advances in LLMs and Gen-AI technologies, we are transforming the very core of how customers can effortlessly interact with our offerings to build and operate their applications in the cloud.

We are hiring to grow our team in Seattle (Washington), and are looking for well-rounded applied scientists with backgrounds in machine learning, foundation models, and natural language processing.

You'll be working with talented scientists, engineers, and product managers to innovate on behalf of our customers. If you're fired up about being part of a dynamic, mission driven team, then this is your moment to join us on this exciting journey!

Key job responsibilities

As a Sr. Applied Scientist you will be responsible for

• Research and development of algorithms that improve training of foundation models across pre-training, multitask learning, supervised finetuning, and reinforcement learning from human feedback
• Research and development of novel approaches for anomaly detection, root cause analysis, and provide intelligent insights from vast amounts of monitoring and observability data
• Collaborating with scientists, engineers, and Product Managers across CloudWatch team as well as directly with customers
• Lead key science initiatives in strategic investment areas of AI / ML / LLM Ops and Observability
• Be an industry thought leader representing Amazon at top-tier scientific conferences
• Engaging in the hiring process and developing, growing, and mentoring junior scientists

A day in the life

Working closely with and across agile teams, you will be able to see and feel the impact of your work on our customers. This is a high visibility and high impact role that will interact with all levels of AWS leadership.

Our ideal candidate is excited about the incredible opportunity that cloud monitoring represents and is deeply passionate about delivering the highest quality services leveraging AI / ML / LLMs.

You’re naturally customer centric and thrive in a fast-paced environment that requires strong technical and business judgment and solid communication skills.

About the team

Amazon CloudWatch Logs is a core monitoring service used by millions of AWS customers. We move fast and have delivered remarkable products and features over the last few years to streamline how AWS customers troubleshoot their critical applications.

Our mission is to be the most cost effective, integrated, fast, and secure logs management and analytics platform for AWS customers.

We are a diverse group of product and engineering professionals that are passionate about delivering logging features that delight customers operating at any scale.

Mentorship & Career Growth

Our team is dedicated to supporting new members. We have a broad mix of experience levels, and we’re building an environment that celebrates knowledge sharing and mentorship.

We care about your career growth and strive to assign projects based on what will help each team member develop into a better-rounded product manager and enable them to take on more complex tasks in the future.

Work / Life Balance

Our team puts a high value on work-life balance. It isn’t about how many hours you spend at home or at work; it’s about the flow you establish that brings energy to both parts of your life.

We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment.

We offer flexibility in working hours and encourage you to find your own balance between your work and personal lives.

Inclusive Team Culture

Our team is intentional about attracting, developing, and retaining amazing talent from diverse backgrounds. We’re looking for a new teammate who is enthusiastic, empathetic, curious, motivated, reliable, and able to work effectively with a diverse team of peers;

someone who will help us amplify the positive & inclusive team culture we’ve been building.

Here at AWS, we embrace our differences. We are committed to furthering our culture of inclusion. We have ten employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally.

We have innovative benefit offerings, and we host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences.

Amazon’s culture of inclusion is reinforced within our 14 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust.

BASIC QUALIFICATIONS

• PhD, or Master's degree and 6+ years of applied research experience
• 3+ years of building machine learning models for business application experience
• Experience programming in Java, C++, Python or related language
• Experience with neural deep learning methods and machine learning
• Ability to translate informal customer requirements into problem definitions, dealing with ambiguity and competing objectives.

PREFERRED QUALIFICATIONS

• Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.
• Experience with large scale distributed systems such as Hadoop, Spark etc.
• Excellent written and verbal communication skills, with the ability to present complex technical information in a clear and concise manner to a variety of audiences.
30+ days ago