Product Trainer Jobs

We’re building a world of health around every individual — shaping a more connected, convenient and compassionate health experience. At CVS Health®, you’ll be surrounded by passionate colleagues who care deeply, innovate with purpose, hold ourselves accountable and prioritize safety and quality in everything we do. Join us and be part of something bigger – helping to simplify health care one person, one family and one community at a time. Position Summary The primary responsibility of an Inventory Control Coordinator – Specialty Returns is the daily processing of patient returns. This includes evaluating both authorized and unauthorized returned patient shipments to determine if products will be credited to the patients accounts and if the products can be returned to stock, reshipped to patients, returned to the manufacturer, or destroyed. Additional responsibilities include: - Documenting daily returns by notating patient accounts and updating appropriate systems. - Monitoring pump inventory for issues and scheduled maintenance. - Receiving manufacturer replacement product and noting patient accounts. - Reviewing received manufacturer recalls and taking appropriate actions. - Supporting the Materials Management team as needed. Required Qualifications • One year experience in a pharmacy environment. • One year computer experience in a Windows based system. • Valid state pharmacy technician or technician trainee license. Preferred Qualifications • Excellent organizational skills. • Attention to detail. • Excellent communication and interpersonal skills. • Ability to work in a team environment. • Ability to work independently. • Excellent math aptitude. • Excellent problem solving skills. • Ability to lift

We’re building a world of health around every individual — shaping a more connected, convenient and compassionate health experience. At CVS Health®, you’ll be surrounded by passionate colleagues who care deeply, innovate with purpose, hold ourselves accountable and prioritize safety and quality in everything we do. Join us and be part of something bigger – helping to simplify health care one person, one family and one community at a time. Position Summary The primary responsibility of an Inventory Control Coordinator – Specialty Returns is the daily processing of patient returns. This includes evaluating both authorized and unauthorized returned patient shipments to determine if products will be credited to the patients accounts and if the products can be returned to stock, reshipped to patients, returned to the manufacturer, or destroyed. Additional responsibilities include: - Documenting daily returns by notating patient accounts and updating appropriate systems. - Monitoring pump inventory for issues and scheduled maintenance. - Receiving manufacturer replacement product and noting patient accounts. - Reviewing received manufacturer recalls and taking appropriate actions. - Supporting the Materials Management team as needed. Required Qualifications • One year experience in a pharmacy environment. • One year computer experience in a Windows based system. • Valid state pharmacy technician or technician trainee license. Preferred Qualifications • Excellent organizational skills. • Attention to detail. • Excellent communication and interpersonal skills. • Ability to work in a team environment. • Ability to work independently. • Excellent math aptitude. • Excellent problem solving skills. • Ability to lift

About Mixpanel Mixpanel is the leading product intelligence and analytics platform, trusted by more than 29,000 companies to help understand how people use the products they build. By combining powerful analytics with AI that knows your business, Mixpanel helps teams see what’s working, diagnose what’s not, and decide what to build next. Learn more at mixpanel.com . About the Customer Engineering Team Mixpanel’s Customer Engineering teams are analytics consultants who embed themselves within our enterprise customer teams to drive business outcomes. We work with prospects and customers throughout the customer journey to understand what drives value, and serve as the technical counterpart to our Sales organisation to deliver on that value. You will partner closely with Account Executives, Customer Value Architects, Product, Engineering, and Support to successfully roll out self-serve analytics within our customers’ organisations, help manage change, execute on technical projects and services that delight our customers, and ultimately drive ROI on the customer’s Mixpanel investment. About the Role Our Customer Engineers are inquisitive, nimble, and able to clearly articulate the technical benefits and requirements of Mixpanel to developers and product managers, while also communicating the business value of our product to senior executives. In your first month, you’ll become a Mixpanel expert—both in features and functionality as well as implementation. You’ll shadow customer calls and demos with current Customer Engineers and Account Executives while learning to articulate our value proposition, and be trained on Mixpanel’s internal systems and tools. Within your first three months, you’ll be directly involved in deal cycles with Account Executives across the ANZ region. You’ll lead the technical qualification for customer use cases and deliver customised demos for prospects and existing customers, working directly with leadership at the prospect’s organisation to und

About the Team The Personal AGI team is responsible for training and improving pre-trained models to be deployed into ChatGPT, the API, and potential future products. The team partners closely with research and product teams across the company, and conducts research as a final step to prepare for real world deployment to millions of users, ensuring that our models are safe, efficient, and reliable. About the Role As a Research Engineer / Scientist, you will research and develop improvements to our models. Our team works in research areas combining reinforcement learning and products. We're looking for individuals with strong ML engineering skills and research experience, especially with novel and highly capable models. An ideal candidate is passionate about product-driven research. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: Own and pursue a research agenda to improve model capability and performance. Collaborate closely with the other research and product teams, allowing customers to optimize their own models. Build robust evaluations for tracking modeling improvements. Design, implement, test, and debug code across our research stack. You might thrive in this role if you: Have a deep understanding of machine learning and machine learning applications. Have a working knowledge of relevant models, and building evaluations for model capability improvement. Are comfortable diving into a large ML codebase to debug. Thrive in a dynamic and technically complex environment. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and

About the Team The Personal AGI team is responsible for training and improving pre-trained models to be deployed into ChatGPT, the API, and potential future products. In the Model Experience team, we shape the default character and behavior of ChatGPT: how the model communicates, responds to users, uses its capabilities, and behaves across different contexts and languages. Our goal is to make every interaction with ChatGPT thoughtful, helpful, and trustworthy. We take an opinionated view of what good human–AI interaction should look like, then turn that vision into real model behavior through human data, evaluations, reward models, and post-training. Our work sits at the intersection of research, product, and model design. We partner closely with teams across OpenAI to conduct research and ensure our models are thoughtful, safe, reliable to serve millions of users. About the Role As a Research Engineer / Scientist, you will research and develop improvements to our models. Our team works in research areas combining reinforcement learning and products. We're looking for individuals with strong ML engineering skills and research experience, especially with novel and highly capable models. An ideal candidate is passionate about product-driven research and the quality of human-AI interaction. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: Own and pursue a research agenda to improve model capability and performance. Collaborate closely with the other research and product teams, allowing customers to optimize their own models. Build robust evaluations for tracking modeling improvements. Design, implement, test, and debug code across our research stack. You might thrive in this role if you: Have a deep understanding of machine learning and machine learning applications. Have good judgment about model behavior and can communicate this judgment effec

About the Team OpenAI's research training infrastructure powers how our frontier models are trained and evaluated. The Simulation team sits at the intersection between the agentic harness that powers OpenAI's products and the research infrastructure where GPT-next is trained, ensuring that our model's training environment is as realistic as possible. This team owns the integration layer that connects our production harness capabilities into the training stack. The work is highly cross-functional and high leverage: researchers depend on it to run experiments and evaluations reliably as well as to develop the next generation of harness capabilities. Failures in this surface can materially affect training velocity and correctness. About the Role We're looking for a Principal Software Engineer to lead the architecture and evolution of the Simulation Platform. You'll own a critical interface between research and engineering, building the systems, APIs, and operational patterns that let researchers use agentic coding infrastructure safely and effectively in training environments. This role is ideal for a senior backend or infrastructure engineer with strong technical judgment, product sense for highly technical users, and the ability to drive execution across multiple teams. The highest-leverage work is building robust infrastructure that supports and accelerates research without compromising engineering quality. In this role, you will Design, build, and evolve the integration between the Codex harness that powers OpenAI's products and research training infrastructure used for training GPT-next Build a platform for our LLMs to train and be evaluated in simulated environments that mimic their deployment setting as closely as possible, on every axis: agentic harness, compute substrate, timing, tools, data sources, humans in the loop, and more Own major integration surfaces end-to-end, from architecture and API design through rollout, operations, and long-term maintenance Bu

About the Team OpenAI's Human Data Team creates custom data solutions driving groundbreaking research. Our work enhances and evaluates our flagship models and products like ChatGPT, GPT-5, and Sora, and contributes to safety initiatives through collaboration with our Preparedness and Safety Systems teams. About the Role As a Research Program Manager (RPM) in the Human Data team you will partner with research and engineering to design and implement pragmatic solutions for collecting high-quality data. You will be a key interface between our research roadmap, external vendors, AI trainers, and the Human Data engineering team. This role is based in our San Francisco HQ. In this role, you will: Collaborate with Research: Partner with researchers to scope data collection needs, define success metrics, and establish quality measurement frameworks. Design & Execute Data Collection Campaigns: Translate research needs into actionable plans and accelerate execution by leveraging existing tooling and iterating to reach the desired outcome. In many cases, you will need to implement scrappy new solutions while partnering with engineering to design robust/scalable solutions. Unblock Yourself: You must be deeply uncomfortable with the idea of sitting around waiting for external dependencies, and have the technical acumen and drive to figure out how to achieve at least partial success in the interim. Optimize Systems & Processes: Build and optimize dashboards to track campaign performance, leveraging SQL and Python for data analysis and actionable insights. Drive Technical Roadmaps: Collaborate with engineers to enhance data platforms, resolve blockers, and ensure security best practices such as access management. Scale Your Impact : Advise and empower program managers and vendors to drive day-to-day execution so that you can focus on addressing high priority opportunities. You might thrive in this role if you: Are proficient in SQL and Python for data analysis, including q

#TeamNextdoor Nextdoor (NYSE: NXDR) is the essential neighborhood network. Neighbors, public agencies, and businesses use Nextdoor to connect around local information that matters in more than 350,000 neighborhoods across 11 countries. Nextdoor builds innovative technology to foster local community, share important news, and create neighborhood connections at scale. Download the app and join the neighborhood at nextdoor.com . Meet Your Future Neighbors As a Data Scientist at Nextdoor, you will help design and oversee product experiments and own complex analyses to drive company and product strategy. We use a semi-embedded team structure, in which a group of data team members works on a specific product or pillar, interfacing directly with product and engineering stakeholders. The Data Science group consists of people from a diverse set of backgrounds and perspectives, trained in fields as wide-ranging as economics, physics, statistics, and operations research. We are an integral part of the product development organization and play an active and collaborative role in building and improving the product. At Nextdoor, we operate in an AI-first environment and expect every team member to actively use AI tools as part of their workflow. We aren't looking for prompt engineers; we’re looking for people who use tools like Claude, Gemini, ChatGPT, and Glean to challenge their own thinking and take full ownership of AI-assisted outputs. We also offer a warm and inclusive work environment that embraces a hybrid employment model, blending an in office presence and work from home experience for our valued employees. The hiring team will go over these expectations with you if you are being considered for a role near one of our offices in San Francisco, Los Angeles, Chicago, Dallas, New York, and London. The Impact You'll Make We are looking for a Staff Data Scientist to accelerate execution on priority content investments and elevate the quality of product decision-making.

#Team Nextdoor Nextdoor (NYSE: NXDR) is the essential neighborhood network. Neighbors, public agencies, and businesses use Nextdoor to connect around local information that matters in more than 350,000 neighborhoods across 11 countries. Nextdoor builds innovative technology to foster local community, share important news, and create neighborhood connections at scale. Download the app and join the neighborhood at nextdoor.com . Meet Your Future Neighbors As Data Scientists at Nextdoor, you will have the opportunity to influence strategic decisions with product analytics, drive better experimentation and build online and offline ML solutions. We use a semi-embedded team structure, with data team members interfacing directly with product and engineering stakeholders. The Data Science group is made up of people from a diverse set of backgrounds and perspectives, trained in fields as wide-ranging as economics, psychology, geography, physics, statistics, and operations research. We are the mathematical decision scientists for the product development organization and play a proactive and collaborative role in building and improving the product. At Nextdoor, we operate in an AI-first environment and expect every team member to actively use AI tools as part of their workflow. We aren't looking for prompt engineers; we’re looking for people who use tools like Claude, Gemini, ChatGPT, and Glean to challenge their own thinking and take full ownership of AI-assisted outputs. We also offer a warm and inclusive work environment that embraces a hybrid employment model, blending an in office presence and work from home experience for our valued employees. The hiring team will go over these expectations with you if you are being considered for a role near one of our offices in San Francisco, Los Angeles, Chicago, Dallas, New York, and London. The Impact You’ll Make As a Senior Data Scientist on the Search team, you will shape how neighbors find the people, places, posts, and business

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 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

About the Team The Agent Infrastructure team at OpenAI is responsible for building systems that enable training and deployment of highly useful AI agents, both internally and for the world. We work hand-in-hand with researchers to design and scale the environment in which agentic models are trained – providing a workspace for AI models to execute code, debug issues, and develop software just as human SWEs do. Our training environment for agentic models operates at an extremely high scale and has the flexibility to emulate any environment in which an agent might work. At the same time, our team builds and maintains OpenAI’s core platform for the deployment and execution of agents in production. Our systems power products such as Codex, Operator, tool use in ChatGPT, and future agentic products. Some of the most challenging technical problems in scaling the capabilities and utility of agents and agentic models lie in the infrastructure layer – and our team is focused on building the research and production systems that enable OpenAI to train the most capable models in the world, and maximize the utility of our agentic products for users around the world. About the Role As a Software Engineer on the Agent Infrastructure team, you will have the opportunity to work closely with both research and product at OpenAI - building and scaling systems to train highly capable agentic models, and building the platform and integrations to launch new agents to hundreds of millions of users worldwide. Your work will consist of both building new capabilities - standing up the infrastructure and integrations needed to train more complex agentic models - and rapidly scaling these new capabilities to some of the largest compute clusters in the world. At the same time, you’ll be instrumental to the launch of agentic products at OpenAI - building, maintaining, and scaling the production platform on which all agents run. We’re looking for people with deep experience building AI infrastructu