Lead Senior Python Engineer Jobs

Location Details: At GoDaddy the future of work looks different for each team. Some teams work in the office full-time, others have a hybrid arrangement (they work remotely some days and in the office some days) and some work entirely remotely. Remote: This is a remote position, so you’ll be working remotely from your home. You may occasionally visit a GoDaddy office to meet with your team for events or meetings. Join our team Our Global Sustaining Engineering team sits at the intersection of software engineering and infrastructure, ensuring the services our customers depend on are fast, resilient, and always available. As a Senior Site Reliability Engineer, you'll take direct ownership of production services — from initial design through day-to-day operation — while partnering with product, engineering, and security teams to build and maintain business-critical systems. In this role, you will deepen your technical expertise and grow your leadership presence by mentoring the next generation of SREs. You will also gain hands-on experience with intelligent tooling in real-world workflows. What you'll get to do... Design, implement, and operate scalable, highly available production services while diagnosing and resolving complex infrastructure, network, and application issues Build and maintain alerting pipelines, dashboards, and SLO-driven monitoring strategies using Icinga, Prometheus, and Grafana Lead incident response end-to-end — performing root-cause analysis, authoring blameless post-mortems, and driving corrective actions to closure Develop and extend Infrastructure as Code coverage and build internal tooling that eliminates manual, repetitive operational work Mentor SRE I and SRE II engineers through code reviews, debugging sessions, and knowledge-sharing talks Apply LLM-driven log analysis, anomaly detection, and generative AI tools to accelerate incident response and runbook creation — validating all outputs before use Your experien

As a Key Accounts Enterprise Sales Engineer, you will provide technical expertise through sales presentations, product demonstrations, and supporting technical evaluations (POVs). Sales Engineers help qualify and close opportunities with customers and partners and have a voice with the product team to help prioritize features based on input from customers, competitors, and partners. What You’ll Do: Partner with the Sales, Product/Engineering, Customer Success, Professional Services, and executive leadership to articulate the overall Datadog value proposition, vision and strategy to customers Lead technical strategy for both short-term and long-cycle pursuits by driving the end-to-end technical sales agenda for Fortune 100 and comparable prospects — from pipeline generation through purchase decision Technically close complex opportunities through advanced competitive knowledge, technical skill, and credibility Present at executive and technical forums, lead workshops, and translate technical detail to business impact for CIOs, SRE/Platform teams, security/compliance, and engineering leadership Maintain accurate notes and feedback in CRM regarding customer input both wins and losses Proactively engage and communicate with customers and Datadog business/technical teams regarding product feedback and competitive landscape Who You Are: Passionate about educating customers on observability risks that are meaningful to their business, and able to build and execute an evaluation plan with a customer Someone with strong written and oral communication skills. This role requires an ability to understand and articulate both the business benefits (value proposition) and technical advantages of our offering Experienced in programming/scripting with one or more languages (i.e. Python, Go, Java, etc.) and familiarity with DevOps practices such as CI/CD and IaC workflows Demonstrated ability to land into net new logo accounts and collaborate with prospects through long, multi-quarte

We're transforming the grocery industry At Instacart, we invite the world to share love through food because we believe everyone should have access to the food they love and more time to enjoy it together. Where others see a simple need for grocery delivery, we see exciting complexity and endless opportunity to serve the varied needs of our community. We work to deliver an essential service that customers rely on to get their groceries and household goods, while also offering safe and flexible earnings opportunities to Instacart Personal Shoppers. Instacart has become a lifeline for millions of people, and we’re building the team to help push our shopping cart forward. If you’re ready to do the best work of your life, come join our table. Instacart is a Flex First team There’s no one-size fits all approach to how we do our best work. Our employees have the flexibility to choose where they do their best work—whether it’s from home, an office, or your favorite coffee shop—while staying connected and building community through regular in-person events. Learn more about our flexible approach to where we work. Overview As a Senior Machine Learning Engineer II on the Ads Response Prediction team, you will lead the design and development of core ML models that power Instacart’s ads ecosystem. This is a research-leaning role focused on theoretical problem formulation, training methodology, and model quality rather than infrastructure or full-stack engineering. You will tackle fundamental challenges in pCTR modeling such as mitigating selection bias, position bias, and optimizer’s curse in training data, improving model calibration across surfaces and domains, and advancing our multi-task learning and sequence modeling capabilities. You will also have the opportunity to shape our next-generation foundation model approach for ads ranking and contribute to cutting-edge retrieval systems like TIGER (Transformer Index for Generative Recommenders), Semantic ID and domain language

Ready to do the most impactful work of your career? At Coinbase , we are uncompromising on our mission to increase economic freedom. The bar is high, the environment is intense, and we like it that way. This isn't a place for complacency, it’s a place to be pushed past your perceived limits. If you're ready to build the future of finance alongside people who refuse to settle for "good enough," you belong here. Coinbase is a remote-first, but not remote-only company. Expect to get together quarterly for intense in-person working sessions called “surges.” learn more about working at Coinbase . As a Senior Staff Software Engineer on the Platform Payments team, you'll define the engineering vision for how fiat moves into and out of Coinbase across 50+ countries and payment rails. This team builds and operates the fiat on- and off-ramps, routing, orchestration, and funds-flow services that power every customer-facing payment experience. You'll own the multi-quarter technical strategy, architect for global scale and reliability, and drive platform-level improvements that directly impact payment success rates, latency, and cost efficiency. What you'll do: Define and drive the multi-quarter technical strategy for Payments spanning rails, orchestration, and transfers to support new products, geos, and significant growth in payment volume. Architect and evolve the core Payments platform (rails integrations, routing, and funds-flow services) for high availability, low latency, and cost efficiency at global scale. Lead end-to-end design and rollout of large, cross-team initiatives (e.g., new global rails, decomp/migrations, resiliency programs), breaking ambiguity into clear milestones and measurable outcomes. Set and enforce technical standards for financial correctness across Payments, including idempotency, reconciliation, failure-mode handling, and auditability for all money-movement paths. Partner with FinHub, Payments Risk, Regulatory Platform, and Produc

Ready to do the most impactful work of your career? At Coinbase , we are uncompromising on our mission to increase economic freedom. The bar is high, the environment is intense, and we like it that way. This isn't a place for complacency, it’s a place to be pushed past your perceived limits. If you're ready to build the future of finance alongside people who refuse to settle for "good enough," you belong here. Coinbase is a remote-first, but not remote-only company. Expect to get together quarterly for intense in-person working sessions called “surges.” learn more about working at Coinbase . Payments Platform is at the front door of Coinbase’s financial ecosystem. Our mission is to move old money into crypto and power financial access and payments for the crypto economy globally. As the bridge between the traditional financial world and the crypto economy, we build and operate the fiat on- and off-ramps and payment services that let Coinbase’s customer-facing products deliver reliable, seamless payment processing and connect customer fiat funds into crypto. We’re seeking a deep technical leader to define the engineering vision for Payments, shape architectural cohesion across our global payment rails and funds-flow systems, drive platform-level reliability and cost efficiency, and lead the next evolution of how fiat moves into and out of Coinbase. What you’ll be doing (ie. job duties): Define and drive the multi‑quarter technical strategy for Payments, spanning rails, orchestration, and transfers, to support new products, geos, and significant growth in payment volume. Architect and evolve the core Payments platform (rails integrations, routing, and funds-flow services) for high availability, low latency, and cost efficiency at global scale. Lead end‑to‑end design and rollout of large, cross‑team initiatives (e.g., new global rails, decomp/migrations, resiliency programs), breaking high ambiguity into clear milestones and measurable outcomes. Set and enf

Ready to do the most impactful work of your career? At Coinbase , we are uncompromising on our mission to increase economic freedom. The bar is high, the environment is intense, and we like it that way. This isn't a place for complacency, it’s a place to be pushed past your perceived limits. If you're ready to build the future of finance alongside people who refuse to settle for "good enough," you belong here. Coinbase is a remote-first, but not remote-only company. Expect to get together quarterly for intense in-person working sessions called “surges.” learn more about working at Coinbase . As a Machine Learning Engineer on the CX Intelligence team within Enterprise Applications and Architecture, you'll build the AI-powered conversational systems that connect Coinbase's Help Center, chatbots, and agent workflows. The team owns the multi-agent platform powering Coinbase Chat and agent tooling, partnering with Conversation Design, CX, and Engineering to deliver secure, scalable automated support. You'll lead the design and implementation of a unified orchestration layer that coordinates interactions between vendor AI, internal multi-agent systems, and human participants, directly improving how millions of customers get help. What you'll do: Architect and deploy the orchestration layer that manages state transitions, context sharing, and intent routing across vendor and internal LLM frameworks in a distributed conversational environment. Build production-grade Python services that bridge advanced ML/AI research with reliable, measurable customer-facing products. Lead end-to-end project execution for complex ML initiatives, managing priorities, technical trade-offs, and cross-functional dependencies from design through delivery. Establish best practices for system design, coding standards, and AI/ML development workflows across the team. Mentor engineers on architectural integrity and modern AI/ML patterns, raising the technical bar for the broader team. Co

Ready to do the most impactful work of your career? At Coinbase , we are uncompromising on our mission to increase economic freedom. The bar is high, the environment is intense, and we like it that way. This isn't a place for complacency, it’s a place to be pushed past your perceived limits. If you're ready to build the future of finance alongside people who refuse to settle for "good enough," you belong here. Coinbase is a remote-first, but not remote-only company. Expect to get together quarterly for intense in-person working sessions called “surges.” learn more about working at Coinbase . The CX Intelligence team is part of Coinbase’s Enterprise Applications and Architecture org and builds the customer-facing and internal CX experiences that connect the Help Center, chatbots (CBCB), and agent workflows. The team owns the multi-agent platform which powers coinbase chat, Help Center and agent tooling surfaces, partnering closely with Conversation Design, CX, and other Engg teams to deliver secure, compliant, and scalable AI-powered support. Our work provides the trusted and accurate automated and agent-assisted experiences—helping customers get answers faster while enabling human agents to resolve cases more effectively. We are hiring an IC5 Machine Learning Engineer to drive the evolution of our conversational ecosystem by building a seamless hybrid vendor-internal chatbot experience. You will lead the design and implementation of a sophisticated unified orchestration layer that coordinates interactions between vendor AI, internal multi-agent systems, and human participants. This role is pivotal in managing complex state transitions, context sharing, and intent routing across a distributed environment. You’ll thrive here if you enjoy high ownership, architecting complex hand-off logic between disparate LLM frameworks, and building reliable AI-enabled products that are fast, measurable, and scalable. What you'll do: Architect and deploy the orchestratio

At Lyft, our mission is to improve people's lives with the world's best transportation. To accomplish this, we start with our community by creating an open, inclusive, and diverse organization. About the Team The Risk Tech engineering organization is committed to tangibly reducing accident frequency, saving lives, and managing costs to enhance the safety and affordability of rides. Claim Management is a core financial function for Lyft. Each claim touches complex workflows, multiple stakeholders, sensitive data, financial reserves, regulatory processes, and significant financial liabilities. This role offers the opportunity to define a leading claims management system for the industry. Our vision is to establish a single, Unified Risk Platform where comprehensive claims workflows across all business lines are efficiently administered, communications are consolidated, and data is structured to facilitate data-driven insights and decisions.This enables cost-efficient claims operations, mitigates risks and expenses as Lyft scales, and ensures people receive assistance proactively and accurately. About the Role We are seeking a Senior Software Engineer to contribute to the technical direction, drive architectural decisions, and lead the development of a highly reliable, scalable, and intelligent Risk Management Information System that powers our insurance platform. You will collaborate with passionate colleagues from Engineering, Data Science, Product and Claim Operations to deliver end-to-end solutions. Responsibilities: Define and drive the long-term technical roadmap for claims management systems, aligning priori

At Lyft, our mission is to improve people's lives with the world's best transportation. To accomplish this, we start with our community by creating an open, inclusive, and diverse organization. About the Team The Risk Tech engineering organization is committed to tangibly reducing accident frequency, saving lives, and managing costs to enhance the safety and affordability of rides. Claim Management is a core financial function for Lyft. Each claim touches complex workflows, multiple stakeholders, sensitive data, financial reserves, regulatory processes, and significant financial liabilities. This role offers the opportunity to define a leading claims management system for the industry. Our vision is to establish a single, Unified Risk Platform where comprehensive claims workflows across all business lines are efficiently administered, communications are consolidated, and data is structured to facilitate data-driven insights and decisions.This enables cost-efficient claims operations, mitigates risks and expenses as Lyft scales, and ensures people receive assistance proactively and accurately. About the Role We are seeking a Senior Software Engineer to contribute to the technical direction, drive architectural decisions, and lead the development of a highly reliable, scalable, and intelligent Risk Management Information System that powers our insurance platform. You will collaborate with passionate colleagues from Engineering, Data Science, Product and Claim Operations to deliver end-to-end solutions. Responsibilities: Define and drive the long-term technical roadmap for claims management systems, aligning priori

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 a billion rides per year and counting, Lyft is solving hard problems in a rapidly growing domain with a lot of data and creative solutions in Rider, Marketplace, Growth, and beyond. While traditional approaches to optimization and problem decomposition are sufficient to disrupt transportation, building a next-generation platform for low-cost, ultra-immersive transportation to improve people's lives warrants modern ML utilizing peta-byte scale data. Our highly motivated Machine Learning Engineers work on these challenging problems and define solutions to directly impact various aspects of our core business. If you are a critical thinker with experience in machine learning workflows and LLMs, passionate about solving business problems using data and working in a dynamic, creative, and collaborative environment, we are searching for you. We are seeking a Senior Machine Learning Engineer to join the Rider Applied AI team and lead the design, development, and deployment of state-of-the-art machine learning and artificial intelligence systems. This role requires a strategic thinker who can balance high-level system architecture with hands-on technical implementation. You will collaborate across teams to shape the future of ride-sharing by leveraging AI, Machine learning and Data science. Responsibilities: Model Development & Research: Design, build, and deploy machine learning models for real-time applications, including translating state-of-the-art research into production-ready solutions. System Design: Architect scalable, reliable ML pipelines that integrate seamlessly with existing backend systems. Innovation & Applied Research: Stay ahead of the curve by exploring emerging algorithms, technologies (such as LLMs and LLM-based applications), and frameworks — critically eva

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 a billion rides per year and counting, Lyft is solving hard problems in a rapidly growing domain with a lot of data and creative solutions in Rider, Marketplace, Growth, and beyond. While traditional approaches to optimization and problem decomposition are sufficient to disrupt transportation, building a next-generation platform for low-cost, ultra-immersive transportation to improve people's lives warrants modern ML utilizing peta-byte scale data. Our highly motivated Machine Learning Engineers work on these challenging problems and define solutions to directly impact various aspects of our core business. If you are a critical thinker with experience in machine learning workflows and LLMs, passionate about solving business problems using data and working in a dynamic, creative, and collaborative environment, we are searching for you. We are seeking a Senior Machine Learning Engineer to join the Rider Applied AI team and lead the design, development, and deployment of state-of-the-art machine learning and artificial intelligence systems. This role requires a strategic thinker who can balance high-level system architecture with hands-on technical implementation. You will collaborate across teams to shape the future of ride-sharing by leveraging AI, Machine learning and Data science. Responsibilities: Model Development & Research: Design, build, and deploy machine learning models for real-time applications, including translating state-of-the-art research into production-ready solutions. System Design: Architect scalable, reliable ML pipelines that integrate seamlessly with existing backend systems. Innovation & Applied Research: Stay ahead of the curve by exploring emerging algorithms, technologies (such as LLMs and LLM-based applications), and frameworks — critically eva

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 is looking for experienced software engineers from a variety of disciplines. We are growing our team with people who want to build, improve and incorporate technologies that make the lives of our community more enriched. As an engineer at Lyft, you'll collaborate with teams like product, data science, analytics, and operations on code that empower us to iterate quickly, while focusing on delighting our passengers and drivers. As a Senior Software Engineer on the Marketplace team, you will lead work streams to improve business operations in Lyft’s Marketplace. You'll design AI driven data analytics platforms, data pipelines and metric governance systems that our business leaders use on a daily basis to make key strategic decisions. You will partner with business leaders and data scientists across our organizations to enable running the business more efficiently. Responsibilities: Help define the roadmap and architecture based on technology and business needs Drive AI innovation for business analytics and operations Write well-crafted, well-tested, readable, maintainable code Have a good grasp and ability to explain the various tradeoffs made in decisions Participate in code reviews to ensure code quality and distribute knowledge Lead projects from idea to positive execution Incorporate considerations for business context and failure modes in your work Proactively participate in resolving ongoing incidents Unblock, support, effectively communicate, and obtain buy-in across teams to achieve results Share your knowledge by giving brown bags, tech talks, and evangelizing appropriate tech and engineering best practices Experience: 5+ years of software engineering industry experience with a high level programming language (bonus points for experience with Python or Go) AI Experience in Agen

Airbnb was born in 2007 when two hosts welcomed three guests to their San Francisco home, and has since grown to over 5 million hosts who have welcomed over 2 billion guest arrivals in almost every country across the globe. Every day, hosts offer unique stays and experiences that make it possible for guests to connect with communities in a more authentic way. The Community You Will Join: BizTech fosters culture and connection at Airbnb by providing reliable corporate tools, innovative products, and technical support for all teams. We drive technical breakthroughs and strategies that redefine what it means to belong anywhere, delivering greater value for the business and our people. The Global Operations team at BizTech manages production services across Airbnb’s corporate environment, delivering reliable operations through Observability, Incident Management, Core Operations, and AI-enabled automation. We partner across BizTech to scale service quality, efficiency, and resilience. The Difference You Will Make: As a Senior Staff Engineer in Operations, you will lead and mentor a high-performing team to scale our AI-enabled operations model and deliver AIOps solutions that streamline operational workstreams and help BizTech teams focus on their core work with confidence. Ops owns triage and resolution, proactive monitoring across networks, systems, applications, and cloud services via a homegrown observability platform, and drives process excellence through automation and shift-left programs. You will set the technical bar, model operational excellence, and ensure high-quality, reliable service. Your scope includes leading projects ac

Airbnb was born in 2007 when two hosts welcomed three guests to their San Francisco home, and has since grown to over 5 million hosts who have welcomed over 2 billion guest arrivals in almost every country across the globe. Every day, hosts offer unique stays and experiences that make it possible for guests to connect with communities in a more authentic way. The Community You Will Join: The Host Pricing & Settings team builds the platform and tools that help hosts run their business — with pricing strategies informed by market intelligence, comparable listings, and demand signals. We partner with Search, Listings, Tax, and Payments to ensure our guidance is accurate, timely, and trusted. Behind every pricing recommendation is a sophisticated ML system undergoing a fundamental rearchitecture. Our north star: a serving infrastructure where training, inference, and evaluation are consistent by design — features from a centralized store, model composition in one place, and backfills available on demand so data scientists and MLEs can evaluate candidates in days, not weeks. The Difference You Will Make: As a senior technical individual contributor, you will own the technical strategy for the full Modeling → ML Serving → API interface across the Host Pricing org. Although you will be at one of our highest levels of seniority, all individual contributors at Airbnb are Software Engineers — you are expected to be hands-on and contribute code. Define the architecture and contracts governing how models move from development to production — feature store design, model schema management, online/offline inference consistency, and multi-version support. Lead the buildout of a unified serving stack that eliminates per-model one-off implementations and gives data scientists a turnkey path from training to production. Architect backfill and evaluation infrastructure so the modeling team can simulate production inference over historical data in days, not weeks. Establish do