Trainee Supervisor Jobs

We are a global team of innovators and pioneers dedicated to shaping the future of observability. At New Relic, we build an intelligent platform that empowers companies to thrive in an AI-first world by giving them unparalleled insight into their complex systems. As we continue to expand our global footprint, we're looking for passionate people to join our mission. If you're ready to help the world's best companies optimize their digital applications, we invite you to explore a career with us! Your opportunity Join our team as a Partner Solution Consultant, a critical role within the Customer Advocacy (CA) technical field organization. You will serve as the primary technical arm for the Partner Sales Go-To-Market (GTM) engine, supporting our sales managers and ecosystem partners. In this role, you are the "quarterback" for all partner engagements within your assigned region. Your mission is to ensure our partners, including resellers, SIs, and MSPs, are technically capable, successful in selling, and effective in delivering our observability solutions across the entire partner lifecycle. You will balance technical enablement and solution support with rigorous delivery governance to drive partner-sourced revenue, ramp consumption and maximize customer impact. What you'll do Partner Enablement & Capability Building: Design and execute structured enablement plans for assigned partners, delivering workshops, "train-the-trainer" sessions, and technical coaching to close skill gaps and build technical autonomy. Solutioning & Pre-Sales Support: Act as an observability architect and "Swat Team" member for high-value partner-led opportunities, assisting with complex solution design, demonstrations, and Proofs of Value (POVs). Ecosystem Orchestration: Serve as an "air traffic controller" between internal teams (AEs, SCs, TSMs) and partners to determine the best route to success for every customer opportunity sourced by Partners. Operational Management: Maintain projec

We are a global team of innovators and pioneers dedicated to shaping the future of observability. At New Relic, we build an intelligent platform that empowers companies to thrive in an AI-first world by giving them unparalleled insight into their complex systems. As we continue to expand our global footprint, we're looking for passionate people to join our mission. If you're ready to help the world's best companies optimize their digital applications, we invite you to explore a career with us! Your opportunity Join our team as a Partner Solution Consultant, a critical role within the Customer Advocacy (CA) technical field organization. You will serve as the primary technical arm for the Partner Sales Go-To-Market (GTM) engine, supporting our sales managers and ecosystem partners. In this role, you are the "quarterback" for all partner engagements within your assigned region. Your mission is to ensure our partners, including resellers, SIs, and MSPs, are technically capable, successful in selling, and effective in delivering our observability solutions across the entire partner lifecycle. You will balance technical enablement and solution support with rigorous delivery governance to drive partner-sourced revenue, ramp consumption and maximize customer impact. What you'll do Partner Enablement & Capability Building: Design and execute structured enablement plans for assigned partners, delivering workshops, "train-the-trainer" sessions, and technical coaching to close skill gaps and build technical autonomy. Solutioning & Pre-Sales

The Team + The Role Mind the Product Training helps organizations build better products by connecting them with product management expertise, training, and advisory services. Through a network of trainers and product leaders, the team helps companies improve how they develop products, operate as data-driven organizations, and evolve in the era of AI. As Sr. Program Manager, Mind the Product Training, you will build and deliver customer training programs that are well-scoped, operationally strong, and aligned to customer goals. You will partner with the Director of Mind the Product, Program Management colleagues, customers, trainers, advisors, and internal stakeholders to shape solutions, operationalize engagements, and deliver a consistently high-quality customer experience. This role is not responsible for writing individual class content. This is a role based in-office in San Francisco or Raleigh or Remote in the United States. What this looks like day-to-day Training opportunity assessment: Partner with the Director of Mind the Product to qualify inbound training opportunities and shape program approaches that address specific customer business challenges. Translate customer goals into practical engagement structures that can be delivered effectively. Program operations and delivery: Coordinate the onboarding of training customers, gather key engagement details, schedule sessions, and manage the operational steps required for smooth delivery. Facilitate trainer selection based on the client’s industry, location, and training needs while ensuring trainers receive the background needed to customize delivery. Pre-training readiness: Manage pre-training communication with clients to collect attendee lists, schedule sessions and send attendees pre-class materials. Post-class follow-up: Collect feedback from attendees, trainers, and clients after each engagement. Generate client feedback reports that summarize key takeaways, performance metrics, and opportunities to im

For over 20 years, Smartsheet has empowered teams to manage work seamlessly and scale solutions smarter. Now, in our most ambitious chapter yet, we are uniting human teams with AI agents. By orchestrating the work agents do best, automating manual tasks and uncovering insights at scale, we create the space for people to focus on what truly matters: judgment, creativity, and big thinking. That is magic at work, and it’s what we show up for every day. Smartsheet is hiring a Senior Machine Learning Operations Engineer to architect our machine learning production lifecycle. Your mission is to maintain and deploy ML models to a scalable, reliable, and secure production environment. You will design and maintain the infrastructure, automation, and monitoring systems that ensure our AI products are high-performing and cost-effective. You will report to our Director, Analytics Engineering & Data Governance and work from our Bangalore, India office. You Will: Model and Pipeline Automation Automate the deployment and retraining of ML models, from training through to production inference, by building and managing complete CI/CD/CT (Continuous Training) pipelines, adhering to MLOps best practices. Build, fine-tune, or use pre-trained LLMs, deep learning models or traditional machine learning models. Evaluate and recommend AI or ML solutions for the product using any combination of vendor solutions and/or custom-built models. Governance & Compliance Implement model versioning, lineage tracking, and auditing to ensure compliance with security and ethical standards. Performance Monitoring Continuously monitor the health and performance of production machine learning models, proactively identifying and correcting model drift, staleness, and performance degradation. Incorporate user feedback for iterative improvements and manage necessary model retraining cycles. Cross-Functional Collaboration Act as the "glue" between Data Scientists (who build models

As a Research Scientist on our team, you will partner with Research Engineers, working on fundamental research problems and collaborating with Datadog's product and engineering teams to translate research advances into products. Building on our track record of AI-powered solutions (e.g., Bits AI , Bits Evolve , and our time series foundation model ), Datadog AI Research tackles high-risk, high-reward problems grounded in real-world challenges in cloud observability and security. We are focused on two research areas: World Models for Observability -- Training multimodal foundation models that learn the joint dynamics of distributed systems across metrics, traces, logs, topology, and events. These models power advanced forecasting, anomaly detection, root cause analysis, counterfactual simulation ("what if?"), and provide a learned planning backbone for our autonomous agents. Trained Agents for Observability -- Post-training models to operate autonomously across Datadog's domain. SRE incident response is our first target, with a clear path to code repair, security response, and infrastructure optimization. We build the simulation environments, RL training loops, and evaluation infrastructure needed to train agents that match or surpass frontier models at a fraction of the cost. What You'll Do: Conduct research in generative AI and machine learning, building specialized foundation models and trained agents for observability Train multimodal models on large-scale, diverse telemetry data (metrics, logs, traces, topology, events) using distributed training infrastructure Design and build simulated environments and RL training loops for on-policy agent training and evaluation Collaborate with cross-functional teams (Product, Engineering) to integrate capabilities like multimodal world modeling and autonomous agents into Datadog's products Stay at the forefront of foundation models, world models, and RL-based agent research Contribute to r

As a Research Scientist on our team, you will partner with Research Engineers, working on fundamental research problems and collaborating with Datadog's product and engineering teams to translate research advances into products. Building on our track record of AI-powered solutions (e.g., Bits AI , Bits Evolve , and our time series foundation model ), Datadog AI Research tackles high-risk, high-reward problems grounded in real-world challenges in cloud observability and security. We are focused on two research areas: World Models for Observability -- Training multimodal foundation models that learn the joint dynamics of distributed systems across metrics, traces, logs, topology, and events. These models power advanced forecasting, anomaly detection, root cause analysis, counterfactual simulation ("what if?"), and provide a learned planning backbone for our autonomous agents. Trained Agents for Observability -- Post-training models to operate autonomously across Datadog's domain. SRE incident response is our first target, with a clear path to code repair, security response, and infrastructure optimization. We build the simulation environments, RL training loops, and evaluation infrastructure needed to train agents that match or surpass frontier models at a fraction of the cost. What You'll Do: Conduct research in generative AI and machine learning, building specialized foundation models and trained agents for observability Train multimodal models on large-scale, diverse telemetry data (metrics, logs, traces, topology, events) using distributed training infrastructure Design and build simulated environments and RL training loops for on-policy agent training and evaluation Collaborate with cross-functional teams (Product, Engineering) to integrate capabilities like multimodal world modeling and autonomous agents into Datadog's products Stay at the forefront of foundation models, world models, and RL-based agent research Contribute to r

As a Staff Technical Program Manager, you will partner with key Engineering, Product, Product Design, Marketing, and Analytics stakeholders to deliver Observability features and platform capabilities for MongoDB. As a seasoned program leader, you will be responsible for one of our most mission-critical programs this fiscal year, and own executive level communication related to the program. We are looking to speak to candidates who are based in Dublin for our hybrid working model. The right candidate for this role will be: Experienced with 10+ years of working in an engineering organization leading complex cross-functional technical programs Experienced with 5 years of Software development background, with Cloud storage and compute products Experience with Service Oriented Architecture and Cloud Infrastructure Able to leverage their knowledge and experience to influence technical discussions, summarizing outcomes and next steps Skilled at communicating across a diverse set of engineers and stakeholders Hyper-organized and capable of coordinating across multiple independent work streams and organizations A role model for effective execution practices, driven by an attuned sense of priority and urgency Able to leverage their experience in program delivery to influence improvements to our tools, operations, and architecture Trained in working with project tracking software (e.g. Jira, Rally, MS Project) Familiar with MongoDB or a comparable technology Interested in business automation work such as scripting in Python, Google Apps Script and Slack. Position Expectations: Leverage technical acumen and analytical skills to drive engineering programs forward and maximize business value delivery Recognize patterns in a sea of information and take action accordingly Design, maintain, and improve the processes and tools that power program delivery Build strategic partnerships with Product and Engineering stakeholders Expand knowledge into new domains as called upon Act as a me

As a Research Engineer on our team, you will partner with Research Scientists to turn research ideas into working systems, building the data, tooling, and infrastructure that enable rapid iteration, trustworthy evaluation, and a smooth path from prototype to production. Building on our track record of AI-powered solutions (e.g., Bits AI , Bits Evolve , and our time series foundation model ), Datadog AI Research tackles high-risk, high-reward problems grounded in real-world challenges in cloud observability and security. We are focused on two research areas: World Models for Observability -- Training multimodal foundation models that learn the joint dynamics of distributed systems across metrics, traces, logs, topology, and events. These models power advanced forecasting, anomaly detection, root cause analysis, counterfactual simulation ("what if?"), and provide a learned planning backbone for our autonomous agents. Trained Agents for Observability -- Post-training models to operate autonomously across Datadog's domain. SRE incident response is our first target, with a clear path to code repair, security response, and infrastructure optimization. We build the simulation environments, RL training loops, and evaluation infrastructure needed to train agents that match or surpass frontier models at a fraction of the cost. What You'll Do: Build and operate multimodal data pipelines, training and evaluation infrastructure, benchmarks, and internal tooling Implement models, run experiments at scale, and profile for reliability, performance, and cost Build simulation environments and replay infrastructure for agent training and evaluation Orchestrate distributed training and distributed RL with Ray, including scheduling, scaling, and failure recovery Establish rigorous automated benchmarks and regression tests for world model predictions, agent performance, and simulation fidelity Collaborate with Research Scientists, Product, and Engineeri

As a Sr. Staff Technical Program Manager, you will partner with key Engineering, Product, Product Design, Marketing, and Analytics stakeholders to conduct data-driven experiments and deliver features for MongoDB. As a seasoned program leader, you will be responsible for one of our most mission-critical programs this fiscal year, and own executive level communication related to the program. We are looking to speak to candidates who are based in Dublin or Cork for our hybrid working model, or remote within Ireland. The right candidate for this role will be: Experienced with 15+ years of working in an engineering organization leading complex cross-functional technical programs Experienced with 10 years of Software development background, with Cloud storage and compute products Experience with Service Oriented Architecture and Cloud Infrastructure Able to leverage their knowledge and experience to influence technical discussions, summarizing outcomes and next steps Skilled at communicating across a diverse set of engineers and stakeholders Hyper-organized and capable of coordinating across multiple independent work streams and organizations A role model for effective execution practices, driven by an attuned sense of priority and urgency Able to leverage their experience in program delivery to influence improvements to our tools, operations, and architecture Trained in working with project tracking software (e.g. Jira, Rally, MS Project) Familiar with MongoDB or a comparable technology Interested in business automation work such as scripting in Python, Google Apps Script and Slack Position Expectations: Leverage technical acumen and analytical skills to drive engineering programs forward and maximize business value delivery Recognize patterns in a sea of information and take action accordingly Design, maintain, and improve the processes and tools that power program delivery Build strategic partnerships with Product and Engineering stakeholders Expand knowledge into new

As a Sr. Staff Technical Program Manager, you will partner with key Engineering, Product, Product Design, Marketing, and Analytics stakeholders to conduct data-driven experiments and deliver features for MongoDB. As a seasoned program leader, you will be responsible for one of our most mission-critical programs this fiscal year, and own executive level communication related to the program. We are looking to speak to candidates who are based in Dublin or Cork for our hybrid working model, or remote within Ireland. The right candidate for this role will be: Experienced with 15+ years of working in an engineering organization leading complex cross-functional technical programs Experienced with 10 years of Software development background, with Cloud storage and compute products Experience with Service Oriented Architecture and Cloud Infrastructure Able to leverage their knowledge and experience to influence technical discussions, summarizing outcomes and next steps Skilled at communicating across a diverse set of engineers and stakeholders Hyper-organized and capable of coordinating across multiple independent work streams and organizations A role model for effective execution practices, driven by an attuned sense of priority and urgency Able to leverage their experience in program delivery to influence improvements to our tools, operations, and architecture Trained in working with project tracking software (e.g. Jira, Rally, MS Project) Familiar with MongoDB or a comparable technology Interested in business automation work such as scripting in Python, Google Apps Script and Slack Position Expectations: Leverage technical acumen and analytical skills to drive engineering programs forward and maximize business value delivery Recognize patterns in a sea of information and take action accordingly Design, maintain, and improve the processes and tools that power program delivery Build strategic partnerships with Product and Engineering stakeholders Expand knowledge into new

Who we are About Stripe Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world's largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone's reach while doing the most important work of your career. About the team Bridge is creating an entirely new payments platform, built with stablecoins, to simplify global money movement. Bridge enables faster, cheaper payments and borderless access to dollars via stablecoins. Through our APIs, businesses can send and receive funds across borders faster and cheaper than SWIFT and other fiat-only rails. Our virtual accounts enable international consumers and businesses to easily access, store, and spend US dollars. Our payouts infrastructure enables platforms to disburse USD to anyone globally. We believe many trillions of dollars will move and settle through stablecoin payment rails. Bridge is pulling this future forward. The Stripe Finance and Strategy team is an integral thought partner to Stripe's core functional leaders. We bring understanding and predictability to Stripe's bottom-line financials. We work cross-functionally across many surfaces at Stripe and help steward Stripe's resource investments to improve the durability of our long-term financial performance. This role will partner closely with Bridge, a small team of people experienced in building financial infrastructure at leading companies. What you'll do We are looking for a Strategic Finance Partner who combines the rigor of a trained financial analyst with the technical self-sufficiency to answer complex business questions independently. This is a high-ownership, high-exposure role. You will own business forecasting, pricing analytics, and cross-fu

About the Team The Artifacts team is building the AI-native creation layer for documents, spreadsheets, slide decks, dashboards, reports, analyses, and new forms of interactive work products. We are rethinking what creation looks like when models can move from an ambiguous user goal to a polished, editable artifact with strong structure, taste, correctness, and speed. This is a high-agency team working across product, infrastructure, and research. We partner closely with model training teams to shape how frontier models create artifacts, and with ChatGPT product teams to turn those capabilities into experiences that millions of people can use. The work spans full-stack product engineering, model integration, rendering and editing systems, collaboration, storage, evaluation loops, and production reliability. Our ambition is to build the premier product experience for AI-generated artifacts: starting with familiar work products like slides, sheets, and docs, then expanding into new artifact types that are only possible in an AI-native world. About the Role As Engineering Manager, Artifacts, you will lead and grow the engineering team responsible for building this product and technical foundation. You will manage a team of full-stack and infrastructure-oriented engineers, set technical direction, and stay hands-on enough to shape architecture and debug hard problems. This role sits at the intersection of product engineering, research, and infrastructure. You will partner with researchers on how models are trained and evaluated for artifact creation, with product and design on the user experience. This is a strong fit for a technical manager who wants to build and ship, not only coordinate. The team has a fast trajectory, so you will help define both the product surface and the team that builds it. In this role, you will: Lead, manage, and grow a team building AI-native artifact creation experiences across documents, spreadsheets, slide decks, and emerging artifact form

About the Team The Future of Computing Research team is an applied research team within the Consumer Devices group focused on developing new methods, models, and evaluation frameworks that support our vision for the future of computing. We work at the frontier of multimodal AI, helping turn emerging model capabilities into product experiences that are useful, delightful, and worthy of long-term trust. Our work explores a new class of AI systems that can learn over time, adapt to individuals, and support people in the flow of daily life. This includes long-term memory, user modeling, and personalization systems that are aligned not just with immediate satisfaction, but with a person’s broader goals, values, and well-being. We work closely across research, engineering, design, product, and safety to define what it means to build AI systems that know you over time, act at the right moment, and help in ways that are context-aware, respectful, and demonstrably beneficial. About the Role We are looking for a Research Engineer / Scientist to join the Future of Computing Research team to work on RLHF and post-training for personalized, multimodal AI systems. This role will focus on building the learning and evaluation foundations that help models become more context-aware, adaptive, and useful over time. You will work on problems such as reward modeling, preference learning, long-horizon evaluation, and policy improvement for systems that must make high-quality behavioral decisions in realistic user settings. The work is deeply product-grounded: success is not just higher benchmark performance, but better model behavior in real-world use. The ideal candidate is excited about pushing beyond one-turn assistant behavior toward systems that improve through feedback, learn from richer signals, and are trained against meaningful notions of user value. Internally, that maps closely to the need for careful reward design, feedback loops, and evaluation frameworks that test whether i

Who We Are Notion is the collaborative AI workspace where teams and agents think together . We're building one place where your knowledge, projects, meetings, and AI tools live side by side, so work is faster, clearer, and less fragmented. Millions of individuals, small teams, and large companies run their work on Notion. Notinos (our employees) are customer zero in bringing this future of work to life. We care about craft, building things that last, and the belief that great work is still fundamentally human. Our goal isn’t to ship the next feature. Each and every team of Notinos is working to set the standard for how humans work together in the AI era. From building a business’s system of record to making and managing AI agents to automating away the busy work, we care deeply about giving our customers more time for their life’s work. About the Role: You're joining Notion's People Analytics & Operations team as part of an 18-month rotational program -- the group that builds the insights engine powering every people decision Notion makes. We look for slope over intercept. We care less about where you trained and more about what you've built. If you've ever rebuilt a broken process because it was bothering you, used AI to do something you couldn't have done alone, or found yourself reading about labor economics for fun -- you're the person we're looking for. Over 18 months, you'll rotate across people operations, people analytics, and compensation/benefits. Every rotation is real work with real ownership. On the analytics side, you'll build dashboards that land in exec review, write SQL that powers headcount models, and prototype AI-assisted workflows that help our team move faster. On the operations side, you'll run the HR engine -- managing employee lifecycle transactions in Workday, owning onboarding and offboarding coordination end-to-end, triaging and resolving employee requests, and keeping our people data clean and audit-ready. You'll be paired with a sen

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. THE MISSION We are seeking a Staff Research Scientist to serve as a technical pillar within our AI research organization. You will not just execute on roadmaps—you will define them. At the intersection of autonomous agents and large language models (LLMs) , you will build the models and systems that turn enterprise data into self-directed, decision-making agents —shifting from passive data access to autonomous execution. Our team operates at the frontier of enterprise AI, delivering both state-of-the-art models and production systems , including: Arctic LLM : Enterprise foundation models optimized for performance and efficiency Arctic-Text2SQL : Post-trained reasoning models with frontier-level quality at a fraction of cost and latency Snowflake Intelligence : Brought research to production through agentic innovations in multi-step reasoning, Deep Research for structured and unstructured insights, and system optimization Arctic Inference : High-performance LLM serving stack (Shift Parallelism, SwiftKV), open-sourced and powering Snowflake Cortex Arctic Long-Context Training : Enables 1M+ token context training on a single H200 GPU Agent World Models (AWM) : RL training across 1,000+ synthetic environments for tool-using agents We focus on core challenges such as reliable re