Content Lead Jobs

About Sentry Software runs the world and the pace is faster than ever. Sentry helps developers fix errors and performance issues before users notice, so teams can spend less time firefighting and more time building. Trusted by 200,000+ organizations, Sentry is today’s application monitoring standard and our team is building its AI-native future. About the role Sentry's issue platform processes billions of events every day to help millions of developers find and fix bugs. The hard part is deciding which events point to a problem, which belong together, and what a developer needs to know to investigate. As a Senior Software Engineer on the Issue Detection team, you'll design, build, and operate the systems that make those decisions. You'll work on real-time processing pipelines, monitors, and analysis systems that detect problems and turn them into issues. The work combines distributed systems with product engineering. Choices about detection accuracy and processing latency affect which problems developers see and how soon they can act. You'll help shape how developers monitor their applications and how Sentry groups related events into issues. You'll also build the context developers and AI agents need to investigate what went wrong. Keeping these systems reliable and fast as Sentry grows is part of the job, alongside making the issues they produce more useful. In this role you will Build and scale features on a product surface handling billions of events daily, where both query latency and correctness are immediately visible to users. Own the design and delivery of substantial projects end to end, scoping alongside product and design, making the technical calls within your scope, shipping, and instrumenting what you ship so the team can measure it. You will contribute to meaningful technical product decisions : grouping quality, search performance, migrations and backfills against enormous datasets, and making the surface work well for both humans and agents. Champi

OVERVIEW BENEFITS Medical Dental Vision Employer Paid Basic Employee Life and AD&D Insurance Employer Paid Long Term Disability Flexible Spending Accounts Voluntary Short-Term Disability Voluntary Life and AD&D Insurance Voluntary Accident Insurance Voluntary Critical Illness Insurance EEO At Construction Resources, our people are the driving force behind everything we do. Construction Resources is an equal opportunity employer that aspires to be the best in the business by building an associate experience that celebrates growth, development, and purpose. PHYSICAL DEMANDS The physical demands described here are representative of those that must be met by an employee to successfully perform the essential functions of this job. While performing the duties of this job, the employee is regularly required to speak or hear. The employee is frequently required to sit for extended periods of time, stand, walk, climb stairs, use hands to finger, handle or feel, and reach with hands and arms. Specific vision abilities required by this job include close vision, distance vision, color vision, peripheral vision, depth perception and ability to adjust focus. POSITION TYPE/EXPECTED HOURS OF WORK This is a full-time position that requires overtime as business needs dictate. OTHER DUTIES Please note: this job description is not designed to cover or contain a comprehensive listing of activities, duties, or responsibilities that are required of the employee for this job. Duties, responsibilities, and activities may change at any time, with or without notice. PRIVACY NOTICE We value your privacy and want to ensure transparency regarding the collection and processing of your personal data. As part of our recruitment process, we require your explicit consent to collect, store, and process your personal information, including but not limited to your resume, contact details, professional experience, and other relevant data. This data will be used solely for rec

OVERVIEW BENEFITS Medical Dental Vision Employer Paid Basic Employee Life and AD&D Insurance Employer Paid Long Term Disability Flexible Spending Accounts Voluntary Short-Term Disability Voluntary Life and AD&D Insurance Voluntary Accident Insurance Voluntary Critical Illness Insurance EEO At Construction Resources, our people are the driving force behind everything we do. Construction Resources is an equal opportunity employer that aspires to be the best in the business by building an associate experience that celebrates growth, development, and purpose. PHYSICAL DEMANDS The physical demands described here are representative of those that must be met by an employee to successfully perform the essential functions of this job. While performing the duties of this job, the employee is regularly required to speak or hear. The employee is frequently required to sit for extended periods of time, stand, walk, climb stairs, use hands to finger, handle or feel, and reach with hands and arms. Specific vision abilities required by this job include close vision, distance vision, color vision, peripheral vision, depth perception and ability to adjust focus. POSITION TYPE/EXPECTED HOURS OF WORK This is a full-time position that requires overtime as business needs dictate. OTHER DUTIES Please note: this job description is not designed to cover or contain a comprehensive listing of activities, duties, or responsibilities that are required of the employee for this job. Duties, responsibilities, and activities may change at any time, with or without notice. PRIVACY NOTICE We value your privacy and want to ensure transparency regarding the collection and processing of your personal data. As part of our recruitment process, we require your explicit consent to collect, store, and process your personal information, including but not limited to your resume, contact details, professional experience, and other relevant data. This data will be used solely for rec

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. With over half a billion rides and counting, Lyft is solving hard problems in a flourishing domain with a lot of data and creative solutions in Marketplace, Mapping, Fraud, Growth and beyond. We're actively building the next-generation Machine Learning (ML) platform for low-cost, ultra-immersive transportation to improve people’s lives using modern ML with peta-byte scale data. Our Machine Learning Engineers are excited to work on these challenging problems and redefine solutions to directly impact various aspects of Lyft's primary business. If you are a student with experience in machine learning workflows, passionate about solving challenging problems using data and working in a dynamic, creative, and collaborative environment, this opportunity is for you! Responsibilities: Contribute to the design, build, train and test of Machine Learning models Write production-level code to convert ML models into working pipelines Partner with Product Managers, Data Scientists, and fellow ML Engineers to frame Machine Learning problems within the business context Analyze experimental and observational data, communicate findings to support decisions Participate in code and spec reviews to ensure code quality and distribute knowledge Experience: Currently pursuing a Bachelor's, Master's, or PhD degree in Computer Science or a related technical field from a university in Canada (required) , with a graduation date between December 2027 and Summer 2028 (required). For any candidates who are master's students who worked between their bachelor's and master's programs: candidates should also have less than 2 years of relevant full-time work experience Available during Summer 2027 for the internship in Toronto Good understanding and knowledge of ML libraries like scikit-learn, Tensorflow, PyTorch, Keras, MXNet, et

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. With over half a billion rides and counting, Lyft is solving hard problems in a flourishing domain with a lot of data and creative solutions in Marketplace, Mapping, Fraud, Growth and beyond. We're actively building the next-generation Machine Learning (ML) platform for low-cost, ultra-immersive transportation to improve people’s lives using modern ML with peta-byte scale data. Our Machine Learning Engineers are excited to work on these challenging problems and redefine solutions to directly impact various aspects of Lyft's primary business. If you are a student with experience in machine learning workflows, passionate about solving challenging problems using data and working in a dynamic, creative, and collaborative environment, this opportunity is for you! Responsibilities: Contribute to the design, build, train and test of Machine Learning models Write production-level code to convert ML models into working pipelines Partner with Product Managers, Data Scientists, and fellow ML Engineers to frame Machine Learning problems within the business context Analyze experimental and observational data, communicate findings to support decisions Participate in code and spec reviews to ensure code quality and distribute knowledge Experience: Currently pursuing a Bachelor's, Master's, or PhD degree in Computer Science or a related technical field from a university in Canada (required) , with a graduation date between December 2027 and Summer 2028 (required). For any candidates who are master's students who worked between their bachelor's and master's programs: candidates should also have less than 2 years of relevant full-time work experience Available during Summer 2027 for the internship in Toronto Good understanding and knowledge of ML libraries like scikit-learn, Tensorflow, PyTorch, Keras, MXNet, et

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. Lyft’s Data Science Team builds mathematical models underpinning the platform’s core services. Compared to other technology companies of a similar size, the set of problems that we tackle is incredibly diverse. They cut across optimization, prediction, modeling, inference, transportation, and mapping. We're looking for Masters or PhD students who are passionate about solving mathematical problems with data and are excited about working in a fast-paced, innovative and collegial environment. We are hiring for a variety of Data Science interns, focusing on the following specialties: Optimization: Construct and fit statistical or optimization models that facilitate automated decision making in the app. Machine Learning: Design, build, tune, and deploy machine learning models with a special emphasis on feature engineering and deployment. Inference: Design and analyze tests in our dynamic marketplace, estimating statistical and ML models to enable better decisions, and developing and evaluating algorithmic policies in our pricing, dispatch, and incentives systems. You will report into a Science Manager. Responsibilities: Partner with Engineers, Product Managers, and other cross-functional partners to frame problems, both mathematically and within the business context Perform exploratory data analysis to gain a deeper understanding of the problem Write production modeling code; collaborate with software engineers to implement algorithms in production Design and run both simulated and live traffic experiments Analyze experimental and observational data; communicate findings including working with partner teams and presentations; facilitate launch decisions Experience: Currently pursuing a Masters or PhD degree at a university in Canada (required) in mathematical sciences ( Opera

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. Lyft’s Data Science Team builds mathematical models underpinning the platform’s core services. Compared to other technology companies of a similar size, the set of problems that we tackle is incredibly diverse. They cut across optimization, prediction, modeling, inference, transportation, and mapping. We're looking for Masters or PhD students who are passionate about solving mathematical problems with data and are excited about working in a fast-paced, innovative and collegial environment. We are hiring for a variety of Data Science interns, focusing on the following specialties: Optimization: Construct and fit statistical or optimization models that facilitate automated decision making in the app. Machine Learning: Design, build, tune, and deploy machine learning models with a special emphasis on feature engineering and deployment. Inference: Design and analyze tests in our dynamic marketplace, estimating statistical and ML models to enable better decisions, and developing and evaluating algorithmic policies in our pricing, dispatch, and incentives systems. You will report into a Science Manager. Responsibilities: Partner with Engineers, Product Managers, and other cross-functional partners to frame problems, both mathematically and within the business context Perform exploratory data analysis to gain a deeper understanding of the problem Write production modeling code; collaborate with software engineers to implement algorithms in production Design and run both simulated and live traffic experiments Analyze experimental and observational data; communicate findings including working with partner teams and presentations; facilitate launch decisions Experience: Currently pursuing a Masters or PhD degree at a university in Canada (required) in mathematical sciences ( Opera

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. Lyft’s Data Science Team builds mathematical models underpinning the platform’s core services. Compared to other technology companies of a similar size, the set of problems that we tackle is incredibly diverse. They cut across optimization, prediction, modeling, inference, transportation, and mapping. We're looking for Masters or PhD students who are passionate about solving mathematical problems with data and are excited about working in a fast-paced, innovative and collegial environment. We are hiring for a variety of Data Science interns, focusing on the following specialties: Optimization: Construct and fit statistical or optimization models that facilitate automated decision making in the app. Machine Learning: Design, build, tune, and deploy machine learning models with a special emphasis on feature engineering and deployment. Inference: Design and analyze tests in our dynamic marketplace, estimating statistical and ML models to enable better decisions, and developing and evaluating algorithmic policies in our pricing, dispatch, and incentives systems. You will report into a Science Manager. Responsibilities: Partner with Engineers, Product Managers, and other cross-functional partners to frame problems, both mathematically and within the business context Perform exploratory data analysis to gain a deeper understanding of the problem Write production modeling code; collaborate with software engineers to implement algorithms in production Design and run both simulated and live traffic experiments Analyze experimental and observational data; communicate findings including working with partner teams and presentations; facilitate launch decisions Experience: Currently pursuing a Masters or PhD degree in mathematical sciences ( Operations Research, Computer Science, Statistic

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. Lyft’s Data Science Team builds mathematical models underpinning the platform’s core services. Compared to other technology companies of a similar size, the set of problems that we tackle is incredibly diverse. They cut across optimization, prediction, modeling, inference, transportation, and mapping. We're looking for Masters or PhD students who are passionate about solving mathematical problems with data and are excited about working in a fast-paced, innovative and collegial environment. We are hiring for a variety of Data Science interns, focusing on the following specialties: Optimization: Construct and fit statistical or optimization models that facilitate automated decision making in the app. Machine Learning: Design, build, tune, and deploy machine learning models with a special emphasis on feature engineering and deployment. Inference: Design and analyze tests in our dynamic marketplace, estimating statistical and ML models to enable better decisions, and developing and evaluating algorithmic policies in our pricing, dispatch, and incentives systems. You will report into a Science Manager. Responsibilities: Partner with Engineers, Product Managers, and other cross-functional partners to frame problems, both mathematically and within the business context Perform exploratory data analysis to gain a deeper understanding of the problem Write production modeling code; collaborate with software engineers to implement algorithms in production Design and run both simulated and live traffic experiments Analyze experimental and observational data; communicate findings including working with partner teams and presentations; facilitate launch decisions Experience: Currently pursuing a Masters or PhD degree in mathematical sciences ( Operations Research, Computer Science, Statistic

About the Team API Frontiers turns OpenAI’s frontier models into production APIs that developers can use to build reliable products and agents. We own the core path connecting models to developers through the Responses API, with a focus on safety, reliability, and speed. Working closely with Research, Safety, Codex, and other API teams, we bring new model capabilities into production and improve them through developer feedback. About the Role We are looking for a backend software engineer to build and operate the services behind the Responses API. You will shape API behavior, bring new capabilities from research into production, and make long-running agent workflows dependable and fast. The work combines distributed systems engineering with product judgment: designing useful developer interfaces, managing staged rollouts, and following production issues through to durable fixes. In this role, you will: Design, build, and operate APIs and backend services that bring frontier model capabilities to developers. Partner with Research, Safety, Codex, and API teams to define API behavior and deliver safe, staged launches. Build API capabilities for agent workflows, including task delegation, context sharing, and parallel execution. Strengthen long-running request reliability across timeouts, cancellation, streaming, and background execution. Improve request-processing performance and tail latency through profiling, efficient systems code, and persistent connections. Turn developer feedback and production failures into better observability, diagnostics, and lasting product improvements. Your background might look something like: 5+ years of experience building and operating backend services or developer-facing APIs in production. Strong software engineering fundamentals, with practical knowledge of distributed systems, concurrency, and asynchronous execution. Ability to diagnose production failures and performance bottlenecks using observability data and profiling. Product

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. We are looking for a Solution Engineer who is accustomed to solving customers’ most complex problems, closing large deals, and positioning organizations to enable Analytics and AI adoption quickly and easily. In this role, you will work directly with the sales team and channel partners to understand the needs of our customers, strategize on how to navigate winning sales cycles, provide compelling value-based demonstrations, product fit conversations, and support enterprise Proof of Concepts. As a Snowflake Solution Engineer, you must share our passion for reinventing the data landscape. You should have a proven track record of helping customers modernize their data stack to unlock Analytics/AI/ML capabilities. You are equally comfortable in both a business and technical context, interacting with executives about Data, Analytics & AI strategies and "talking shop" with technical audiences about implementation. Location: Must be located in or near Bogota, Colombia IN THIS ROLE YOU WILL GET TO: Present Snowflake technology and vision to executives and technical contributors, specifically focusing on how Snowflake serves as the engine for rapid AI innovation. Work hands-on with prospects to demonstrate the value of Snowflake throughout the sales cycle, moving them from initi

Our vision is to transform how the world uses information to enrich life for all. Join an inclusive team passionate about one thing: using their expertise in the relentless pursuit of innovation for customers and partners. The solutions we build help make everything from virtual reality experiences to breakthroughs in neural networks possible. We do it all while committing to integrity, sustainability, and giving back to our communities. Because doing so can fuel the very innovation we are pursuing. Responsibilities and Tasks Product Quality (PQ) Predictive Solutions: Build and productionize machine learning models (classification and regression) to support predictive and prescriptive analytics across semiconductor test and manufacturing processes. Agentic AI and LLM Development: Contribute to the design and implementation of multi-agent systems for PQ workflows, including code generation, automated troubleshooting, and process optimization. Work with retrieval-augmented generation (RAG) pipelines: identify data sources, develop retrieval strategies, and improve context quality for LLM-based applications. Assist in implementing tool-using capabilities, function calling, and agent memory systems. Software Engineering and Productionalization: Develop maintainable code and analytical pipelines suitable for high-volume manufacturing environments. Optimize for performance, latency, and token efficiency. Collaborate with senior team members on testing, deployment, and monitoring. Communicate analytical insights, model behavior, and results clearly to technical and non-technical stakeholders Integ

Who We Are: Being naked is the #1 most sustainable option. We're #2. Since 2009, we've been on a mission to bring sustainable fashion to everyone. Named one of Fast Company’s Brands That Matter and winning a Best Carbon Footprint award, we have big goals like being Climate Positive by 2025 , Circular by 2030 , and pushing the whole industry forward along the way. Our work has gotten love in Drapers and Sourcing Journal , and TIME wrote about how great our CEO, Hali Borenstein, is. Basically, we're saving the Earth and looking damn good doing it. We're a global brand with 50+ stores (and counting) around the world, and our own sustainable factory in LA . We innovate across categories like accessories , swimwear , and sleepwear , and we reach millions of people with campaigns like this , this and this . None of this work is possible without the incredible people behind it. We're a mission-based company that invests in an inclusive culture, so we can innovate together and ensure everyone has the space to grow, thrive, and belong. And starting right now, we want to do all that with you. Work Location/ Schedule: 5 days, M-F On-Site at Vernon office Senior Associate, Product Development (Domestic) What you’ll do: Own sample yardage, trim requests, and Recut PP processes end-to-end, driving on-time fit sample completion and adherence to established timelines. Maintain clear prioritization across all assigned styles, proactively tracking milestones, surfacing risks early, and keeping work in consistent forward motion. Identify issues early, evaluate solutions, and act within scope, escalating to management when tradeoffs require broader alignment. Drive alignment across Design, Merchandising, Pattern Makers, Sample Room, R&D, Purchasing, and Production by delivering clear status, context, and next steps. Ensure accuracy and transparency across PLM (Centric), PIM, and shared trackers, keeping BOMs, development status, and material availability consiste

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. Solution Engineer: Accelerate the AI Data Cloud We are looking for a Solution Engineer who is accustomed to solving customer’s most complex problems and closing large deals. In this role you will work directly with the accounts sales team and channel partners to understand the needs of our customers, strategize on how to navigate winning sales cycles, provide compelling value-based demonstrations, support enterprise Proof of Concepts, and ultimately close business. As a Snowflake Solution Engineer you must share our passion about driving the AI Data Cloud adoption, thrive in a dynamic environment and have the flexibility and willingness to jump in and get things done. You are equally comfortable in both a business and technical context, interacting with executives and talking shop with technical audiences and bridging the gap between audiences when needed. YOUR IMPACT (IN THIS ROLE YOU WILL GET TO): Present Snowflake technology and vision, focusing on the AI Data Cloud and its capabilities, to executives and technical contributors at prospects and customers. Work hands-on with prospects and customers to demonstrate and communicate the value of Snowflake technology throughout the sales cycle, from demo to proof of concept to design and implementation. Immerse yourself in the

About Ramp Ramp is building the smart infrastructure for finance teams, embedded in the transaction flow of every dollar a business spends. We automate how over $200B in annualized spend flows in and out of 70,000+ companies: authorizing payments, flagging risk, categorizing spend, and closing books. The problems are high-stakes, data-dense, and unforgiving. We hire people with high agency and high urgency. We look for slope over intercept. We care less about where you trained and more about what you’ve built. At Ramp, everyone is a builder who owns problems end to end and makes consequential decisions that shape the outcome. The median Ramp customer saves 5% and grows revenue 16% in their first year – far in excess of businesses operating without Ramp. We believe every ambitious company deserves the same. If you want to build systems that directly shape how companies move and manage billions, Ramp is the place to do it. About the Role As a Software Engineer, Forward Deployed, you’ll solve the hardest problems standing between Ramp and the world’s largest and most complex companies — shaping and shipping the product capabilities that unlock our growth upmarket. You'll be part of our Core FDE org, which is an agent-first, high-pace, customer-facing engineering team. On FDE, you will interact directly with customers and deliver solutions end to end — understanding pain points, shaping product decisions, and building agents that autonomously expand Ramp's capabilities. Check out our Engineering Blog and FDE post for more context on our work! What You’ll Do Deliver software end to end that meet the needs of our largest customers — understanding user pain points, scoping product specs, and building agents that autonomously implement solutions. Collaborate closely with Sales, Solutions, Customer Success, and Account Management to close deals, activate customers, and expand the value Ramp provides over time. Drive the core product engineering roadmap through our embedding