Python Backend Engineer Jobs

Replit is the agentic software creation platform that enables anyone to build applications using natural language. With millions of users worldwide, Replit is democratizing software development by removing traditional barriers to application creation. About the Role Replit spreads through companies differently than it does through individuals. One person builds an app, colleagues start using it, a team forms, an admin rolls Replit out more widely, and eventually Sales gets involved. You'll be the data scientist for Replit's enterprise business, covering both the product and the go-to-market motion: how Replit spreads inside organizations, what keeps teams engaged after rollout, which features and signals drive expansion, and how all of that becomes pipeline, revenue, and a reliable forecast. Experimentation is hard here. There are far fewer accounts than users, people within an organization influence each other, and admins control what their teams see. You'll figure out how to learn quickly and rigorously anyway. You'll work with Enterprise Product, Engineering, Sales, Customer Success, RevOps, and Finance, and your work succeeds when it changes a product, GTM, or investment decision. You will: Define how we measure the enterprise business end to end: account-level activation, breadth (share of seats active), depth (apps built, deployed, and shared), collaboration, consumption, and net revenue retention Understand virality inside organizations: how Replit spreads from a first builder to teams through app sharing, invites, and viewers who become builders; quantify within-account network effects and find the levers that accelerate them Explain post-engagement churn: why seats and accounts that engaged at rollout go dormant, separate seat-level decay from account-level risk, and turn it into account health models that give the product and Customer Success early warning and a clear next action Identify the product behaviors and features that precede seat expansion and p

Replit is the agentic software creation platform that enables anyone to build applications using natural language. With millions of users worldwide, Replit is democratizing software development by removing traditional barriers to application creation. About the Role: We're redefining how software is built and who gets to build it. Our mission is to achieve Autonomy for All: making programming accessible, collaborative, and powered by AI. To realize this vision, we need people who are obsessed with understanding how users experience our product and can turn that understanding into decisions that move the needle. You'll directly impact Replit's growth by turning user behavior into actionable insights that shape product strategy, improve activation and retention, and drive sustainable revenue growth across our self-serve and enterprise segments. Who You are You're a data scientist who moves fast and goes deep. You can spin up an analysis in hours that would take others days; not by cutting corners, but because you've built the intuition and technical toolkit to get to the right answer quickly. You're the person who digs past the top-line number to find the confound, questions whether the metric actually measures what people think it does, and pressure-tests your own work before anyone else sees it. You treat experimentation as a craft, not a checkbox. You've felt the pain of underpowered tests and novelty effects, and you have the judgment to get it right. You use AI agents and tools aggressively to multiply your output - writing code, exploring data, generating hypotheses, but you treat every AI-assisted output as a draft, not a deliverable. You know what good analysis looks like and you won't ship anything that doesn't meet that bar. The result is that you operate at a speed and depth that most DS teams can't match. You will: Design and analyze product experiments to evaluate feature launches, onboarding changes, and in-product interventions with rigorous statistical

About Appspace: At Appspace, we’re passionate about creating better work experiences for people everywhere, and we’re looking for people that feel the same way. Our global office locations and flexible work culture help you work wherever and however you’re at your best. Plus, we take the time to help you enjoy your work, build lasting connections, and grow your role. Join the Appspace team and be a part of a culture that’s helping people everywhere love where they work. Your Role as a Cloud Security Engineer : We are seeking a highly skilled Cloud Security Engineer to join our dynamic team. This is a crucial customer-facing role where you will be instrumental in designing, implementing secure cloud configurations, being proactive by recommending security by design standards and, securing complex cloud environments for our clients across Google Cloud Platform (GCP), Microsoft Azure, and Amazon Web Services (AWS), with a strong emphasis on GCP. You will leverage your deep expertise in SaaS security, network security, and compliance to provide strategic guidance and hands-on support, ensuring our clients' cloud infrastructures are robust, resilient, and compliant with industry standards. What You'll Do: Cloud Security Operations: Design, implement, and optimize robust cloud security architectures to enhance, build, monitor and address all security alerts from our SIEM and other security systems. This is an operational role whereby you will be available M-F 8am-5pm EDT and, when needed, on-call shifts on evenings and weekends. Network Security Expertise: Your network security and cloud security expertise will be required to respond to customer questionnaires, customer calls and create artifacts including network diagrams, architecture diagram, data flow diagrams and other artifacts to support customer requests. Strong written skills will be required here and attention to detail. SIEM Integration & Optimization: As a Level-2 Security Operation

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 The Secrets Infrastructure team provides the cryptographic identity and secrets management foundation for Stripe. We build and operate the internal certificate authority that authenticates every person and service at Stripe, and the secrets platform that manages everything from financial partner credentials to infrastructure access keys. We build foundational security infrastructure at scale: our certificate authority issues mTLS client certificate identities for thousands of services and engineers, and our secrets platform and libraries protect access to critical financial systems and external partners across all of Stripe’s codebases, services, and platforms. The technical challenges include building systems with 99.99%+ availability, implementing TLS workload identity and attestation logic for new platforms, and designing secret management tools that are both secure and user-friendly. Our infrastructure must be both reliable and developer-friendly—we maintain libraries in Go, Java, Ruby, and Python. As a small team responsible for critical systems, engineers take on meaningful ownership. Through collaboration with teams across Stripe, you'll build and set direction for the authentication and secrets management underpin identity in distributed systems at scale. Secrets Infrastructure is a fully remote team, with a small presence in the Seattle and New York City offices. We pride ourselves on a friendly, technically rigorous, and supp

Staff Embedded SW/FW Engineer (Bringup) Graphcore is a globally recognised leader in Artificial Intelligence computing systems. The company designs advanced semiconductors and data centre hardware that provide the specialised processing power needed to drive AI innovation, while delivering the efficiency required to support its broader adoption. As part of the SoftBank Group, Graphcore is a member of an elite family of companies responsible for some of the world’s most transformative technologies. We are opening a new AI Engineering Campus in Bengaluru which will play a central role in Graphcore's work building the future of AI computing. Job Summary We have an exciting opportunity to be part of a collaborative, cross-functional development team developing C code used to validate cutting-edge, high-performance AI chips and platforms. You will play a critical role in supporting new product introductions and post-silicon validation. Working within the Post-Silicon Bringup team, you will be involved with bringing first silicon to life, developing code primarily in C to configure and exercise systems and sub-systems on new silicon devices, and working closely with many other teams to help it become a fully characterised and working product, reporting project status/progress to program management on a regular basis. You will have the opportunity to, and be responsible for, leading, mentoring, and providing technical guidance to other engineering team members. In this role, you can leverage your experience and industry knowledge to architect and drive implementation of continuous improvements to test infrastructure and processes. The Team The Post-Silicon Bringup team sits within the Architecture and Validation team, we are responsible for bringup and validation of new silicon when it returns from manufacture, enabling and supporting the production SW and FW teams to bring up their software and supporting the Silicon Characterisation team. Respons

About the Team The Intelligence & Investigations team helps OpenAI understand and respond to the risks that can accompany increasingly capable AI. Our work has two central responsibilities: investigating potential high-severity misuse or harm involving our models, and monitoring and characterizing risks to OpenAI, our users, and the broader world. We bring together analysts, investigators, engineers, and other subject matter experts to turn complex signals into a clearer picture of what matters and support informed action. About the Role As an engineer on Intelligence & Investigations Engineering, you will build the systems that support both sides of this mission: giving OpenAI’s leadership superhuman situational awareness of important risks and developments, and accelerating expert investigators and analysts as they assess potential high-severity misuse or harm. You will design, prototype, ship, and maintain end-to-end products that use OpenAI’s models and infrastructure to make sense of large, complex information environments. These systems will surface meaningful signals, synthesize important developments, and help people make well-informed decisions when the stakes are high. You will work directly with analysts, investigators, and other subject matter experts to understand their needs and build products that make their work faster, more effective, and more scalable. Your engineering work will be central to how the team investigates potential misuse, develops situational awareness, and informs decisions. We’re looking for engineers who combine strong technical and analytical skills with product judgment and the ability to move between rapid prototyping and reliable production systems. You should be comfortable working with ambiguous problems, complex data, and evolving AI capabilities—and excited to build tools that expand what human experts can understand and accomplish. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the

Vous voulez travailler dans le domaine de la technologie dans une banque d'investissement? Une formation diplômante rémunérée, un soutien continu, des opportunités auprès d'employeurs internationaux de premier plan: le programme pour diplômés de l'Alumni vous offre tout ce dont vous avez besoin. (Et ne vous inquiétez pas, il n'y a pas d'obligation de formation, pas de frais de sortie, pas de pièges cachés). Chez mtrois, nous mettons en relation d'excellents diplômés avec de brillantes entreprises internationales. Nous comptons parmi nos clients des banques d'investissement de premier plan et d'autres organisations dans un large éventail de secteurs, de l'assurance aux soins de santé en passant par les voyages. Ce que vous ferez: Le support de production joue un rôle essentiel dans la technologie d'entreprise, des moteurs de trading algorithmique aux rapports réglementaires. C'est un peu comme les soins de santé pour la technologie. En tant qu'analyste du support de production chez mtrois, vous aurez pour mission commune de veiller sur les systèmes et processus techniques sur lesquels les autres équipes comptent. Comment ça marche: Inscrivez-vous en ligne : Remplissez le formulaire en haut de cette page en incluant votre CV. Complétez le processus d’évaluation: Cela impliquera un appel d’introduction avec un membre de notre équipe de talents, un test de résolution de problèmes en ligne et une entrevue finale. Inscrivez-vous au cours de formation en ligne de 6 semaines à temps plein: Attendez-vous à un mélange d’apprentissage de type cours magistral, de travail de groupe collaboratif, de complétions de projets et d’affectations de développement logiciel individuel. Recevez le soutien dont vous avez besoin: Qu’il s’agisse de webinaires sur des domaines techniques clés avec notre équipe de talents, ou de sessions sans rendez-vous avec nos gestionnaires d’expérience de l’académie, vous serez supportées tout au long de votre processus. Accédez à des carrières avec des emp

Who are we? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! Role Overview: Design and implement novel research ideas, ship state of the art models to production, and maintain deep connections to academia and the government. We have one of the highest ratio of compute to engineers in the world. We do not delineate strongly between engineering and research. Everyone will contribute to writing production code and conducting research depending on individual interest and organizational needs. We have all the compute, data, and talent available for you to do your best work. Key Responsibilities: Design, build and scale agentic AI systems for serving mission critical use cases. Research, implement, and experiment with ideas on our supercompute and data infrastructure. Learn from and work with the best researchers in the field. Execute across the full AI stack and ship products to serve public interest. Qualifications: Canadian citizenship and eligibility for security clearance ( required for this role ). Extremely strong software engineering skills. Proficiency in Python and related ML frameworks. Experience training, evaluating, and using (as an end-user) LLMs. Experience using large-scale dis

Who We Are Verkada is transforming how organizations protect their people and places with an integrated, privacy-sensitive AI-powered platform that includes solutions for video security, access control, air quality sensors, alarms, intercoms, and visitor management. We’ve got serious momentum in the market: more than 30,000 customers (including 100+ of the Fortune 500), a $5.8B valuation , more than $1 billion in annualized bookings, and backing from CapitalG, Sequoia Capital, General Catalyst, Felicis Ventures, Next47 and more. Physical AI is one of the most consequential technology shifts of our time, and Verkada is at the center of it. You can look at all kinds of communities to see our platform’s impact in the world. It's the retailer that uses our agentic AI to deter theft before it happens. The warehouse that uses AI-powered alerts to make sure its team is protected on the floor with proper PPE. The school that’s alerted to a threat in real-time and triggers a lockdown in seconds, not minutes. We’re rapidly scaling this impact: today, more than 2 million Verkada devices are deployed across 170+ countries. About the Role Verkada’s Marketing Analytics and Data Science team is looking for a strategic analytics leader to play an integral role in leveraging our data and technology to help our marketing team run better, faster, and smarter. This role operates like an internal strategy consultant, using data to diagnose performance, uncover growth opportunities, evaluate ROI, and turn ambiguous business questions into clear recommendations. Our team works AI-first, using tools like Claude Code alongside SQL, dbt, and Looker to accelerate analysis, automate workflows, and build internal tools. This role reports to our Senior Manager of Data Science and Analytics. We are committed to a thriving in-office culture. This role requires that you be on-site at our HQ in San Mateo 5 days a week. What You'll Do Analyze campaign, channel, segment, and funnel p

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role At Anthropic, we are pioneering new frontiers in AI that have the potential to greatly benefit society. However, developing advanced AI also comes with risks if not properly safeguarded. That's why we are seeking an exceptional Detection and Response engineer that will be on the frontlines to build solutions to monitor for threats, rapidly investigate incidents, and coordinate response efforts with other teams. In this role, you will have the opportunity to shape our security capabilities from the ground up alongside our world-class research and security teams. Responsibilities: Lead cybersecurity Incident Response efforts covering diverse domains from external attacks to insider threats involving all layers of Anthropic’s technology stack Develop and deploy novel tooling that may leverage Large Language Models to enhance detection, investigation, and response capabilities Create and optimize detections, playbooks, and workflows to quickly identify and respond to potential incidents Review Incident Response metrics and procedures and drive continuous improvement Work cross functionally with other security and engineering teams Note: This position will require participation in an on-call rotation You may be a good fit if you: 3+ years of software engineering experience, with security experience a plus and/or 5+ years of detection engineering, incident response, or threat hunting experience A solid understanding of cloud environments and operations Experience working with engineering teams in a SaaS environment Exceptional communication and collaboration skills An ability to lead projects with little guidance

Why RoboForce RoboForce is an AI robotics company developing Physical AI–powered Robo-Labor for dull, dirty, and dangerous work. The company's robots are engineered for demanding industrial environments, with a focus on real-world deployment and scalability. We are looking for a Senior / Staff AI Research Scientist, Foundation Models to advance robotic embodied intelligence. In this role, you will develop algorithms that enable robots to understand their environment, interpret and execute tasks, and communicate seamlessly with humans — with a particular focus on building and training world models that allow robots to predict, plan, and generalize across complex physical tasks. Responsibilities Design and deploy vision-language(-action) models (VLM/VLA) for contextual understanding and generalized robot action policies. Develop and train world models for action-conditioned prediction, long-horizon planning, and environment simulation — enabling robots to reason about the consequences of their actions before execution. Research approaches to improve world model fidelity using multi-modal inputs including vision, language, proprioception, and spatial representations. Develop foundation models with spatial reasoning capabilities to achieve high-precision robotic actions. Integrate multi-modal data sources (vision, language, speech, etc.) to enable natural human-robot communication. Optimize and deploy models as production-grade solutions on RoboForce robotic platforms. Requirements PhD degree in Machine Learning, Robotics, or related field, or Master's degree with 4+ years of relevant experience. Proficiency in Python and deep learning frameworks (e.g., PyTorch, JAX). Expertise in large foundation models (VLM, VLA, etc.). Strong understanding of world model architectures and action-conditioned generative modeling for robot learning. Decent understanding of multimodal models, modern ML architectures (transformers, diffusion models, etc.). Requires 5 d

Role Overview You’re a seasoned Site Reliability Engineer who loves owning complex infrastructure, making things run faster, safer, and with less manual effort. In this Staff‑level role, you’ll design and operate VMware‑based private cloud platforms that power mission‑critical SaaS products used by customers around the world. You’ll work across Linux, Windows Server, networking, storage, and automation frameworks to increase reliability, reduce toil, and modernize a global datacenter environment. You’ll have the scope to set technical direction, build automation at scale, and mentor engineers while staying hands‑on with VMware vSphere, F5/AVI load balancers, and hybrid Active Directory. Here’s a breakdown of what you’ll do (not all of it, just the important stuff) Lead the architecture, deployment, and ongoing optimization of VMware vSphere–based private cloud infrastructure across multiple global datacenters. Design and build automation using PowerShell/PowerCLI, Ansible, Python, and CI/CD tools to streamline provisioning, configuration, and compliance. Administer, harden, and troubleshoot Linux (RHEL/CentOS/Ubuntu) and Windows Server environments that host enterprise and SaaS workloads. Integrate and manage Active Directory for authentication, access control, and service accounts across hybrid on‑prem and cloud environments. Partner with network and security teams to manage firewalls, VPNs, storage, and load balancers (F5 BIG‑IP, AVI/NSX Advanced Load Balancer) for highly available services. Document architectures and runbooks, participate in on‑call and change management, and mentor engineers while influencing long‑term reliability and automation strategy. These are the essentials you’ll need to get an interview 10+ years of experience in systems or infrastructure engineering, including operating large‑scale enterprise or SaaS datacenter environments. Deep hands‑on expertise with VMware vSphere (ESXi, vCenter, DRS, HA, vMotion, distributed switches) in production

About the Role Together AI is building the AI Acceleration Cloud, an end-to-end platform for the full generative AI lifecycle, combining the fastest LLM inference engine with state-of-the-art AI cloud infrastructure. The AI Infrastructure team at Together AI is at the forefront of building and scaling the foundational systems that power our generative AI platform. The storage and observability team is crucial for designing, implementing, and maintaining robust distributed storage solutions, ensuring seamless data access and management. They are also responsible for developing comprehensive observability platforms, providing critical insights into system performance and GPU utilization, and proactively identifying and resolving issues. Responsibilities Design and implement a scalable observability platform (metrics, logs, traces) using tools like Prometheus, Grafana, ClickHouse, ClickStack, and OpenTelemetry, including telemetry data pipelines and log aggregation workflows. Develop automated monitoring, alerting, and anomaly detection systems, including SLIs/SLOs, runbooks, and predictive analytics for critical services. Build and deploy custom observability tools and infrastructure-as-code using Go, Python, Terraform, Ansible, and Helm. Collaborate with engineering teams to enhance distributed tracing and application monitoring, and lead incident response with post-mortem analysis. Define observability best practices. Requirements Expertise in observability platforms (Prometheus, Grafana, ClickStack, OpenTelemetry) and cloud-native monitoring services (AWS, GCP, Azure). Strong programming skills in Go, Python, or similar languages, with proficiency in infrastructure-as-code tools (Terraform, Ansible, Helm). Experience designing, operating, and scaling large-scale distributed systems and pipelines for high-volume data ingestion and real-time querying. Deep understanding of containerization (Docker) and orchestration (Kubernetes). Knowledge of microservices architectu

Who are we? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! Role Overview: Our team is a fast-growing group of committed researchers and engineers. The mission of the team is to build reliable machine learning systems and optimize audio inference serving efficiency using innovative techniques. As an engineer on this team, you will work on advancing core audio model serving metrics, including latency, throughput, and quality by diving deep into our systems, identifying bottlenecks, and delivering creative solutions for audio processing and streaming workloads. You’ll collaborate closely with both the training and serving infrastructure teams to ensure seamless integration between model development and deployment, with a special focus on real-time and streaming audio inference. Please Note: We have offices in Toronto, Montreal, San Francisco, New York, Paris, Seoul and London. We embrace a remote-friendly environment, and as part of this approach, we strategically distribute teams based on interests, expertise, and time zones to promote collaboration and flexibility. You'll find the Model Efficiency team concentrated in the EST and PST time zones, these are our preferred locations. Qualifi

Who are we? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! Role Overview: Our team is a fast-growing group of researchers and engineers focused on building reliable ML systems and pushing the boundaries of LLM inference efficiency. We develop techniques that improve how models execute in production, driving lower latency, higher throughput, and consistent quality across diverse workloads. Please Note: We have offices in Toronto, Montreal, San Francisco, New York, Paris, Seoul and London. We embrace a remote-friendly environment, and as part of this approach, we strategically distribute teams based on interests, expertise, and time zones to promote collaboration and flexibility. You'll find the Model Efficiency team concentrated in the EST and PST time zones, these are our preferred locations. Job Responsibilities: As an engineer on this team, you’ll work across the inference stack to improve core performance metrics by diving deep into model execution, identifying bottlenecks, and developing innovative optimizations. You’ll collaborate closely with modeling and systems teams to experiment, measure, and ship improvements that meaningfully accelerate inference. As the team evolves, you’ll