Role Description As a Commercial Process Excellence Engineer , you’ll play a critical role in improving how we deliver value to our customers—from quote to booking, through implementation, service, and renewal. This is an opportunity to apply industrial engineering and Lean Six Sigma principles to real-world commercial challenges, partnering across Sales, Operations, Finance, Customer Success, and Systems teams to design scalable, customer‑centered processes that improve speed, predictability, and experience. Purpose: - Improve commercial velocity and customer experience by designing, optimizing, and sustaining end‑to‑end commercial processes. As a Commercial Process Excellence Engineer , you will: - Map and analyze current‑state customer journey processes, identifying bottlenecks, handoffs, and failure points across the commercial lifecycle (quote to cash and beyond). - Conduct root‑cause analysis to uncover systemic drivers of friction and variability, translating insights into practical, scalable improvements. - Partner with business and system owners to define, test, and implement future‑state process designs aligned to the Commercial Excellence framework. - Apply Lean Six Sigma and industrial engineering techniques to reduce cycle time, eliminate waste, and improve process predictability and quality. - Create clear, visual process documentation (e.g., swimlane diagrams, value stream maps) and present data‑driven recommendations to senior leadership. - Support performance tracking by defining KPIs, contributing to dashboards, and ensuring improvements are measurable, sustained, and embedded in daily operations. - Collaborate cross‑functionally and regionally to share best practices, drive consistency, and enable scalable process excellence across Omnicell. Qualifications - Bachelor’s degree in Industrial Engineering, Business, Operations Management, or a related discipline. - 3+ years of experience in process improvement, operational excellence, or business transformation roles. Requirements - Lean Six Sigma Black Belt (or equivalent certification and demonstrated experience). - Strong analytical, problem‑solving, and process visualization skills. - Proven ability to influence and communicate with stakeholders at multiple levels of the organization. - Experience in a B2B healthcare technology or life sciences environment. - Familiarity with commercial systems such as Salesforce, Conga, Gainsight, or similar platforms. - Exposure to design thinking or customer journey mapping methodologies. - Advanced proficiency with tools such as Power BI, Minitab, Visio, Lucidchart, and Excel. Benefits - Collaborate: Partnering across Sales, Operations, IT, and Customer teams to design end‑to‑end solutions that work in practice, not just on paper. - Inspire: Using data, visuals, and storytelling to align stakeholders around change and continuous improvement. - Develop: Continuously sharpening your process excellence expertise while sharing best practices with peers. - Execute: Turning analysis into action, driving disciplined implementation and measurable results. - Impact: Challenging the status quo to improve customer experience, commercial speed, and business outcomes.

• Architect and develop Solana programs in Rust, using Anchor and/or native frameworks. • Maintain and extend M0’s existing issuance infrastructure, with a focus on Token-2022 extensions. • Optimize programs for compute unit usage, account size, and transaction packing. • Participate actively in code and design reviews. • Prepare codebases for third-party audits, including writing comprehensive tests, invariants, and fuzz harnesses.

Role Description We are looking for a Machine Learning Engineer who will deliver business value by building new AI Products for Calendly’s customers. You will report to the head of AI and will be responsible for building and operating AI-powered features that create magical experiences for our customers. - Own AI powered features from design through deployment, partnering with product, design, and engineering to scope work and define success metrics. - Understand and share domain knowledge, answering domain specific questions for your product area and documenting what you learn for the team. - Prioritize your work independently, balancing feature development, quality, and maintenance, and communicating tradeoffs clearly. - Proactively seek and offer support to teammates pairing, reviewing, and collaborating to move projects forward. - Understand and troubleshoot our deployment pipelines, including build, test, and release steps for ML services and data pipelines. - Use our monitoring and observability tools to effectively triage alerts and incidents, collaborating with partners to restore service and prevent recurrence, and participate in the team’s on-call rotation and incident response. - Serve as a subject matter expert for the features and services you own, including their data contracts, SLAs, and dependencies. - Be a frequent user of AI Tools and champion of adoption to the rest of the company. Qualifications - 6+ years of industry experience in applied AI/ML and software engineering with a demonstrated track record of shipping and operating AI/ML applications in production. - Experience working on GenAI products architecture/system design and implementation. - Hands-on experience implementing AI/ML solutions for high-traffic, low-latency, large-data applications that produced tangible impact for end users. - Understanding of foundation models and the open-source ecosystem, including model fine-tuning and prompt engineering for real product use cases. - Strong programming (Python / Scala / Java / SQL etc) and data engineering skills. - High level of ownership, and the ability to find a way to success. - Strong verbal and written communication skills. - Authorized to work lawfully in the United States of America as Calendly does not engage in immigration sponsorship at this time. Benefits - Base salary is just one component of Calendly’s total rewards package. - All full-time (30 hours/week) employees are also eligible for our Top Performer Bonus program (or Sales incentive), equity awards, and competitive benefits. Company Description Calendly is registered as an employer in many, but not all, states. If you are located in Alaska, Alabama, Delaware, Hawaii, Idaho, Montana, North Dakota, South Dakota, Nebraska, Iowa, West Virginia, and Rhode Island, you will not be eligible for employment. This role may require occasional travel for company events, team collaboration, or offsites.

Runpod is the foundational platform for developers to build and run custom AI systems that scale. With over 500,000 developers worldwide and an annual recurring revenue run rate exceeding $120M, Runpod operates at the intersection of developer velocity and production-scale AI. Founded in 2022, we’ve grown rapidly by building infrastructure purpose-built for modern AI workloads. Our platform enables teams to move from experimentation to deployment with flexibility across cloud, on-prem, and hybrid environments. As a remote-first, globally distributed company, we are building the infrastructure layer that powers the next generation of AI systems. The Reliability team owns the availability, performance, and operational excellence of Runpod’s global platform. While infrastructure teams build the systems, the Reliability team ensures those systems remain resilient, observable, and scalable under real-world production conditions. This team is responsible for: - Defining and enforcing reliability standards across engineering - Designing incident response processes and improving recovery times - Building observability systems and reliability tooling - Driving SLO adoption and production readiness reviews Reducing operational toil through automation The Reliability team works cross-functionally with Infrastructure, Product Engineering, and Support to ensure our systems remain stable and performant as we scale rapidly. We value proactive problem solving, automation-first thinking, and strong ownership of production systems. As a Site Reliability Engineer on the Reliability team, you will focus on ensuring the stability and resilience of Runpod’s distributed platform. You will partner with engineering teams to improve system design, strengthen observability, and prevent incidents before they happen. This role blends software engineering with production operations. You’ll work on reliability frameworks, SLO design, automation, and production hardening, reducing errors and improving performance across different services and infrastructure. This is a high-impact role central to maintaining trust with developers running critical AI workloads on Runpod. Your Impact - Increase platform uptime and reduce incident frequency and duration - Establish and operationalize SLIs/SLOs across services - Improve MTTR through better tooling, automation, and runbooks - Strengthen production readiness standards - Drive long-term systemic reliability improvements You will influence how reliability is defined and measured across Runpod and help build the operational backbone of the company. Responsibilities:Reliability Engineering - Define and implement SLIs/SLOs for critical services - Lead incident response and coordinate cross-team mitigation efforts - Conduct blameless postmortems and ensure corrective actions are completed - Perform production readiness reviews for new services and features - Identify systemic risks and drive preventative improvements Observability & Monitoring - Design and improve monitoring, alerting, and dashboards (Prometheus, Grafana, etc.) - Improve signal-to-noise ratio in alerts and reduce alert fatigue - Build internal tooling for reliability tracking and reporting - Improve visibility into GPU performance and distributed systems health Automation & Toil Reduction - Automate recurring operational workflows - Build tools and scripts (Python, Go, Bash) to eliminate manual processes - Improve deployment safety through automation and guardrails - Strengthen CI/CD reliability and release processes Cross-Functional Reliability Advocacy - Partner with engineering teams to improve system resilience - Provide guidance on fault tolerance, scalability, and failure handling - Contribute to architectural discussions with a reliability-first mindset Requirements: - 5+ years of experience in SRE, Reliability Engineering, or Production Engineering - Strong Linux systems and Networking expertise - Experience managing containerized production systems - Strong understanding of distributed systems and failure modes - Experience defining and managing SLIs/SLOs - Proven incident response and postmortem leadership experience - Strong scripting or programming skills - Experience with monitoring and alerting systems - Excellent written communication skills - Successful completion of a background check Preferred: - Experience with GPU infrastructure or AI/ML platforms - Experience improving reliability in high-growth or large scale environments - Familiarity with GPU observability tooling - Experience with Infrastructure as Code - Experience working in startup environments - Experience building internal reliability platforms or frameworks What You’ll Receive: - The competitive base pay for this position ranges from $150,000- $200,000 usd. This salary range may be inclusive of several career levels at Runpod and will be narrowed during the interview process based on a number of factors, including the candidate’s experience, qualifications, and location - Meaningful equity in a fast-growing company- everyone on the team receives stock options — your impact drives our growth, and you share in the upside. - Generous medical, dental & vision plans - Flexible PTO- take the time you need to recharge - Most roles are remote work first with an inclusive, collaborative teams utilizing slack as the main form of internal communication - Join a passionate team on the cutting edge of AI infrastructure — where culture, learning, and ownership are at the heart of how we scale. RunPod is committed to maintaining a workplace free from discrimination and upholding the principles of equality and respect for all individuals. We believe that diversity in all its forms enhances our team. As an equal opportunity employer, RunPod is committed to creating an inclusive workforce at every level. We evaluate qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, marital status, protected veteran status, disability status, or any other characteristic protected by law.