We are looking for a senior-level machine learning engineer who is passionate about collaborating with data scientists, product managers and engineers alike. As part of our team, you will help us accelerate the development of new and extension of existing products powered by AI and Machine Learning. We expect you to lead the design and deployment of solutions to host our AI agents, models and services in production, in alignment with our design patterns and best practices to support the business.  This is a very senior position that requires strong skills in communication, cross team collaboration and technical leadership ability. Be a key team member and help continue to drive the AI First future of PagerDuty.

You will be working on high-impact / high-visibility projects and have the opportunity to apply your knowledge to help shape how we enable our various products to leverage the latest machine learning and generative AI capabilities. You’ll succeed by being an effective team player, independently managing time, and demonstrating emotional intelligence as you navigate stakeholder relationships championing and scoping our cross-team initiatives.

How you contribute to our vision: Key Responsibilities

• Build and improve the capabilities that enable and accelerate our machine learning (ML), generative and agentic AI based products 
• Partner with applied scientists and product teams, effectively sharing engineering context and working together to support larger initiatives
• Provide guidance, technical leadership, and mentoring to junior members of the team
• Understand how our products are used and proactively lead the delivery of improvements and enhancements based on customer feedback
• Remain current on the latest ML engineering developments, incorporating new solutions to our existing workflow, continuously improving user experience

Basic Qualifications

• 7+ years of experience building, designing, and shipping machine learning solutions to production
• Experience working with Product teams, ensuring and driving a timely delivery
• Proven software development track record with Python (knowledge of Elixir is a bonus)
• Demonstrated experience with data modeling, database design, extract transform load (ETL) processes, working with unstructured data, and cloud-based data infrastructure
• Experience with workflow management tools such as Apache Airflow and AI/ML observability/evaluations products such as Arize, Datadog, etc
• Familiarity with ML processes (exploration, training, deployment), technologies (services, packages), infrastructure (AWS), ML techniques (e.g., natural language processing, deep learning, generative AI)
• Experience with with pre-trained Large Language Models (LLMs) and AI agents in a production environment
• Passionate about data/ML engineering and displaying effective communication when conveying technical concepts and collaborating with across teams

Preferred Qualifications

• Familiarity with container orchestration systems (e.g., Kubernetes)
• Ability to think through a complex problem, build a solution, and execute that solution with effective change management skills
• Strong sense of ownership and accountability. Ability to design large scale solutions and effectively drive the implementation work across teams and products to solve big customer challenges
• History of presenting technical work at industry conferences, workshops, or meetups, with a demonstrated enthusiasm for sharing knowledge and engaging with the broader MLE community
• Experience leveraging AI tools and techniques to enhance development workflows, automate routine tasks, and improve overall engineering productivity

The base salary range for this position is 150,000 - 252,000 USD. This role may also be eligible for bonus, commission, equity, and/or benefits.

Our base salary ranges are determined by role, level, and location. The range, which is subject to change based on primary work location, reflects the minimum and maximum base salary we expect to pay newly hired employees for the position. Within the range, we determine pay for an individual based on a number of factors including market location, job-related knowledge, skills/competencies and experience.

Your recruiter can share more about the specific offerings for this role, as well as the salary range for your primary work location during the hiring process.