Python Backend Engineer Jobs

A World-Changing Company Palantir builds the world’s leading software for data-driven decisions and operations. By bringing the right data to the people who need it, our platforms empower our partners to develop lifesaving drugs, forecast supply chain disruptions, locate missing children, and more. The Role We are seeking a Senior Software Engineer to join a customer-facing product engineering team focused on developing advanced Command and Control (C2) and Agentic Autonomy Software for Autonomous Systems for use in operational and tactical missions. This role involves building, integrating, and deploying state-of-the-art software solutions that combine sensors, actuators, unmanned vehicles, and intelligent decision-making systems including self-hosted and commercial LLMs to enable users to employ and manage robotic and autonomous systems across a variety of mission sets. You will work alongside other experts in sensing, artificial intelligence, physics and simulations, user experience, and edge system engineering to build and deliver solutions that redefine complex military and civilian mission scenarios in the real world. As a part of this team, you will contribute directly to the development of cloud and edge software to command and control autonomous systems, including interfacing with onboard sensors (radar, cameras, RF, and other modalities) and real-time kinetic and non-kinetic systems for individual and swarms of systems. You will work alongside other experts in sensing, artificial intelligence, and systems engineering to shape solutions that redefine complex area defense scenarios. Core Responsibilities Design, implement, and optimize software for mission-critical autonomous systems using modern technologies and methodologies Develop algorithms to process data from heterogeneous sensors for real-time state estimation and threat detection Build LLM and AI-driven systems capable of assessing threats and rapidly making decisions t

About the Role As a Research Engineer at Metis, you’ll work on building the next generation of autonomous post-training systems that leverage our Mantis platform. You’ll operate at the intersection of cutting-edge ML research and scalable engineering, designing, implementing, and deploying algorithms that improve how AI agents learn from feedback, synthetic data, and real-world interactions. You’ll move seamlessly between papers and production, leading large-scale experiments, creating optimized training pipelines, and helping shape the future of post-training autonomy. You’ll have significant ownership, high compute budgets, and the mandate to push the state of the art in applied reinforcement and preference optimization. What You'll Do Research and help build an autonomous post-training agent leveraging the Mantis platform Design and execute large-scale experiments on synthetic data generation and algorithmic architecture Develop and refine methods for reinforcement learning, reward modeling, and human feedback integration Collaborate cross-functionally with Core and Platform Engineering to deploy and evaluate models in production settings Publish or contribute to leading-edge research in the post-training domain Use tooling and compute efficiently to iterate on experimental pipelines and accelerate research velocity Requirements Deep experience in machine learning, preferably reinforcement learning, post-training, or alignment research Demonstrated research contributions; ideally published papers (ICML, NeurIPS) or public implementations Strong proficiency in Python and ML frameworks (PyTorch, JAX, or TensorFlow) Comfort with distributed training, high-throughput data pipelines, and large-scale experiment management Ability to reason independently, formulate hypotheses, and run experiments from idea → insight → product impact Compensation & Benefits Base: $200,000–$1,000,000 Significant Equity Full medical, dental, and vision Wellness & L&D stipend Eq

About the Team Security is at the foundation of OpenAI’s mission to ensure that artificial general intelligence benefits all of humanity. The Security team protects OpenAI’s technology, people, and products. We are technical in what we build but operational in how we execute, and we support every product and research effort at OpenAI. Our tenets include prioritizing for impact, enabling researchers and developers, preparing for future transformative technologies, and fostering a strong, collaborative security culture. About the Role OpenAI is seeking a Security Software Engineer to join the Infrastructure Security (InfraSec) team. InfraSec safeguards the core of OpenAI’s research and production environments—GPU supercomputing clusters, multi-cloud infrastructure, datacenters, networking, storage, and the critical services that power our frontier AI models. Our charter spans everything from bare-metal hardware and firmware to Kubernetes clusters, service meshes, and the data pathways that carry highly sensitive model weights and user data. As a Security Software Engineer, you will design and build critical foundational services, such as authentication systems, egress/ingress proxies, access brokers, and key management platforms, that demand high standards of reliability, scalability, and software craftsmanship. These systems form the security backbone of OpenAI’s supercomputing environment and must remain robust under intense scale and adversarial pressure. In this role, you will: Architect and implement production-grade security services (e.g., auth services, access brokers, secure proxies, key-management infrastructure) that provide strong guarantees across hardware, operating systems, Kubernetes, networks, and CI/CD. Partner with infrastructure and research engineers to embed security into high-performance compute clusters, enabling rapid model training and deployment without compromising protection. Develop automation and detection tooling to continuously identif

About us We were founded in 2017 with the motivation to reach people globally by giving them unique and unforgettable experiences with disruptive products. Our games have reached over 3.5 billion people. This could only be done by gathering exceptional talent and creating a culture to enhance team spirit and creativity. We are looking for passionate teammates to join our team! About the role The more technology evolves, the more it shapes our lives. We’re looking for AI enthusiasts who are passionate about exploring new technologies and creating innovative, effective solutions to improve the way we work. If you thrive on a “how can we do it better” mindset, we’d love to have you on our team! What you’ll be doing Leading AI research and development for internal product and management solutions (RL agents, segmentation, regression models) Analyzing big data to extract features, segment, and provide actionable insights for management Researching, implementing, and experimenting with self-learning agents in diverse RL environments for product development Following and deploying cutting-edge generational models (including finetuning) for tailored, multi-modal use cases Being at the forefront of ML/DL research and gaining valuable expertise Desired skills and experience Bachelor's degree in Computer Science, Mathematics or a related engineering field Proficiency in Python (TensorFlow or PyTorch) Interest in Generative AI techniques (Diffusers, LoRAs, GANs, Transformer models, etc.) and a desire to develop in this area An always-looking-for-better-ways mindset and the ability to understand team needs to proactively generate solutions Ability to combine technical and business mindsets effectively Passion for Match Villains and mobile puzzle games in general What makes our team so unique Feedback and transparency are at the heart of everything we do Exceptional and passionate people/team members Every idea counts Never-ending learning We never stop asking the questions “why”

Location: Onsite – SoHo, New York City At Vise, we're building the future of investment management—powered by technology and driven by advisor needs. As a Senior Investment Strategist, you will play a key role in shaping our investment research, portfolio design, and platform capabilities. Reporting directly to the Co-CIO and working closely with our investment and product teams, you’ll lead research initiatives, design innovative portfolio strategies, and translate complex investment ideas into scalable, technology-driven solutions. This role is ideal for a highly analytical, market-savvy investment professional who excels at solving complex problems, developing differentiated strategies, and driving thought leadership. You’ll focus primarily on research, portfolio design, and the strategic frameworks that underpin our investment approach—while also collaborating cross-functionally to bring these ideas to life on the Vise platform. While this is a research-forward role, a client-first mindset is essential; you must be equally comfortable communicating with internal stakeholders and engaging with advisors when needed to ensure our solutions meet their evolving needs. What you bring on day one: Experience 5+ years of experience in investment research, portfolio strategy, or asset management Expertise in asset allocation, portfolio construction, risk modeling, or security selection Familiarity with advanced portfolio techniques such as direct indexing, tax optimization, factor investing, and systematic strategies Demonstrated success in developing and scaling investment frameworks or productized solutions Proficiency in Python and SQL to support research workflows, performance analysis, and custom data modeling Bloomberg fluency and experience with portfolio analytics platforms Experience working with product and engineering teams to build investment solutions into digital platforms Experience authoring investment research and/or white papers, or marketing comme

About Glean: Glean is the Work AI platform that helps everyone work smarter with AI. What began as the industry’s most advanced enterprise search has evolved into a full-scale Work AI ecosystem, powering intelligent Search, an AI Assistant, and scalable AI agents on one secure, open platform. With over 100 enterprise SaaS connectors, flexible LLM choice, and robust APIs, Glean gives organizations the infrastructure to govern, scale, and customize AI across their entire business - without vendor lock-in or costly implementation cycles. At its core, Glean is redefining how enterprises find, use, and act on knowledge. Its Enterprise Graph and Personal Knowledge Graph map the relationships between people, content, and activity, delivering deeply personalized, context-aware responses for every employee. This foundation powers Glean’s agentic capabilities - AI agents that automate real work across teams by accessing the industry’s broadest range of data: enterprise and world, structured and unstructured, historical and real-time. The result: measurable business impact through faster onboarding, hours of productivity gained each week, and smarter, safer decisions at every level. Recognized by Fast Company as one of the World’s Most Innovative Companies (Top 10, 2025), by CNBC’s Disruptor 50, Bloomberg’s AI Startups to Watch (2026), Forbes AI 50, and Gartner’s Tech Innovators in Agentic AI, Glean continues to accelerate its global impact. With customers across 50+ industries and 1,000+ employees in more than 25 countries, we’re helping the world’s largest organizations make every employee AI-fluent, and turning the superintelligent enterprise from concept into reality. If you’re excited to shape how the world works, you’ll help build systems used daily across Microsoft Teams, Zoom, ServiceNow, Zendesk, GitHub, and many more. You'll be deeply embedded where people get things done. You'll ship agentic capabilities on an open, extensible stack, with

Secure Every Identity, from AI to Human Identity is the key to unlocking the potential of AI. Okta secures AI by building the trusted, neutral infrastructure that enables organizations to safely embrace this new era. This work requires a relentless drive to solve complex challenges with real-world stakes. We are looking for builders and owners who operate with speed and urgency and execute with excellence. This is an opportunity to do career-defining work. We're all in on this mission. If you are too, let's talk. The Engineering Opportunity We are looking for an experienced Senior Site Reliability Engineer to join Okta's Emerging Products Group (EPG). Our mission is to build highly reliable, scalable, and secure cloud services that our customers can trust. We embrace an automation-first mindset and continuously invest in platform engineering, observability, and operational excellence to enable our engineering teams to move quickly and safely. This role is ideal for an engineer who enjoys solving complex technical challenges at scale, building automation, and improving the reliability of production systems. You will serve as a key contributor within the EPG SRE organization, partnering closely with software engineers, architects, and product teams to design, build, and operate world-class cloud services. The ideal candidate exemplifies the philosophy of "if you have to do it more than once, automate it" and possesses a strong passion for continuous improvement, operational excellence, and software engineering. What You'll Be Doing Reliability & Operations Design, build, and operate large-scale cloud infrastructure and production services. Participate in a global on-call rotation supporting highly available customer-facing systems. Participate in incident response efforts and drive post-incident reviews focused on systemic improvements. Define, measure, and improve Service Level Indicators (SLIs), Service Level Objectives (SLOs), and error budgets. Partner with en

About Cubist: Cubist Systematic Strategies, an affiliate of Point72, deploys systematic, computer-driven trading strategies across multiple liquid asset classes, including equities, futures and foreign exchange. The core of our effort is rigorous research into a wide range of market anomalies, fueled by our unparalleled access to a wide range of publicly available data sources. About the team: The team is focused on systematic equity trading. It is established, yet still pre-trade, offering an exciting opportunity to join at an early stage and be involved in a broad range of development areas. The team members come from a mixture of quant analyst and development backgrounds, using the combination of skills to achieve a common goal. All team members are based in the London office five days a week to maximize communication and interaction. Role and Responsibilities: An ideal growth role to suit a developer looking for additional responsibilities and independence. Responsibilities may include: • Building components for all aspects of live trading and research environments. • Driving automation and robustness of our processes. • Developing robust data checking and handling procedures. • Monitoring and troubleshooting any issues that should arise. • Shared responsibility for timely and correct operation of trading systems. Requirements: • Bachelor’s degree or equivalent in computer science or other STEM discipline • 2+ years commercial experience with Python and its data science libraries on Linux. • Pragmatic balance between attention to detail and delivery focus. • Ability to work with ambiguous requirements. • Self-driven, owning problems while knowing when to seek advice. • Knowledge of finance and trading systems a plus. • Experience with a systems programming language (

About the Team OpenAI’s Financial Engineering (FinEng) team powers how revenue flows through our products—pricing & packaging, checkout, payments, subscriptions, and the financial infrastructure behind them. We partner with Product, Engineering, Risk, Finance, and Go-to-Market to make paying for OpenAI products seamless, reliable, and efficient worldwide. About the Role As a Data Scientist on FinEng, you’ll own the analytics and experimentation that improve our checkout and payments , subscriptions , and pricing & monetization systems. You’ll define the metrics that matter, build the source-of-truth data assets, and design experiments that increase conversion, reduce churn and payment failures, and expand global payment method coverage. Your work will directly influence revenue, customer experience, and how we scale internationally. 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 checkout & payments analytics and experimentation across methods and locales (e.g., bank transfers, emerging rails), improving conversion while monitoring risk and latency. Build and run the experimentation program for in-house checkout—define success metrics and guardrails, execute staged rollouts, and use offline incrementality when online tests aren’t feasible. Create operational visibility and source-of-truth data with FinEng Data Engineering—land team-level metrics, SLAs, and self-serve dashboards that drive proactive action. Lead subscription, retention, and monetization analytics—ship launch-readiness for new subscription features, reduce involuntary churn (e.g., targeted retrials/nudges), and develop elasticity/FX frameworks toward pricing optimality. You might thrive in this role if you have 5+ years in a quantitative role (data science, product analytics, or experimentation) in high-growth or fintech environments Fluency in SQL and Python ,

About the Team Codex is OpenAI’s first-party developer product focused on agentic software engineering. We’re building tools that help engineers design, write, test, and ship code faster—safely and at scale. We partner tightly with research and product to translate model advances into tangible developer productivity. About the Role As a Data Scientist on Codex, you will measure and accelerate product-market fit for AI developer tools. You’ll define what “developer productivity” means for our product, run experiments on new coding models and UX, and pinpoint where the model helps or hurts across languages and tasks. Your insights will directly shape how an entire industry builds software. 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 Embed with the Codex product team to discover opportunities that improve developer outcomes and growth Design and interpret A/B tests and staged rollouts of new coding models and product features Define and operationalize metrics such as suggestion acceptance, edit distance, compile/test pass rates, task completion, latency, and session productivity Build dashboards and analyses that help the team self-serve answers to product questions (by language, framework, repo size, task type) Diagnose failure modes and partner with Research on targeted improvements (model quality signals, user feedback, evals) You might thrive in this role if you have 5+ years in a quantitative role at a developer-facing or high-growth product Fluency in SQL and Python; comfort with experiment design and causal inference Experience defining product metrics tied to user value Ability to communicate clearly with PM, Eng, and Design—and to influence product direction You could be an especially great fit if you have Strong programming background; ability to prototype, run simulations, and reason about code quality Familiarity with IDE/extensi

About the Team OpenAI’s Platform team powers how millions of developers and enterprises build with our models. We provide APIs and agentic solutions used by global startups and fortune 500s. We work closely with product, engineering, design, and go-to-market to build a world-class platform that pushes the frontier of AI capabilities. About the Role As a Data Scientist on the Platform team, you will drive a data-driven culture for OpenAI’s API and B2B solutions. You’ll define the metrics that matter for developer success and enterprise value, measure the impact of new models and features, and partner with PMs and engineers to improve model quality, reliability, latency, and cost. Your work will shape how thousands of products adopt agentic AI. 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 Embed with the Platform product team as a trusted partner, uncovering ways to improve developer experience, reliability, and usage growth Define north-star metrics across the developer funnel (activation, retention, growth), as well as latency/cost guardrails for new features and models Design and interpret A/B tests and controlled rollouts (e.g., new model versions, pricing/limits, new API features, new B2B products) Build source-of-truth dashboards and self-serve data tools for product, engineering, and go-to-market teams Translate product learnings into actionable feedback for Research (e.g., failure modes, eval gaps, model response quality) You might thrive in this role if you have 5+ years in a quantitative role in ambiguous, high-growth environments (platforms, APIs, or B2B products a plus) Depth in SQL and Python, with a track record proposing, designing, and running rigorous experiments Experience defining and operationalizing metrics from scratch (including reliability/latency/cost and safety) Strong cross-functional communication with PMs, enginee

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! Why this role? As a Machine Learning Engineer on our Applied ML team, you will work directly with customers to quickly understand their greatest problems and design and implement solutions using Large Language Models. You’ll apply your problem-solving ability, creativity, and technical skills to close the last-mile gap in Enterprise AI adoption. You’ll be able to deliver products like early startup CTOs/CEOs do and disrupt some of the most important industries and institutions globally! As a Machine Learning Engineer (Applied ML), you will: Plan and execute large-group projects that carry through from ideation to production. Bring cross-functional alignment across engineering, product and other disciplines. Mentor a distributed team of engineers in subject matter expertise. Identify opportunities and gaps in existing models and strategize what to work on. Work closely with product teams to develop solutions. Engage in collaborations with our partner organizations. Assist our legal teams with preparation of patents on developed IP. Join us at a pivotal moment, shape what we build and wear multiple hats! You may be a good fit if y

RDQ426R402 At Databricks, we are passionate about enabling data teams to solve the world’s toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world’s best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers — and customer obsessed — we leap at every opportunity to tackle technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. And we're only getting started. As a Product Manager on the Lakeflow Jobs team , you will shape the future of data-aware orchestration on the Databricks Data Intelligence Platform. Jobs is Databricks’ built-in orchestrator, managing hundreds of millions of workloads every week with 99.95% reliability. It powers ETL, AI/ML, BI, and streaming workloads for thousands of customers. Your focus will be on evolving control-flow capabilities, authoring experiences, and observability features that allow customers to productionize workflows with best practices like source control, code promotion, and system observability. This role requires a deep understanding of orchestration workflows , data pipelines , and service reliability. You will work closely with engineers, designers, field teams, and customers to define the roadmap, drive adoption, and ensure Jobs is the best-in-class orchestration platform for modern data and AI teams. The impact you’ll have: Define strategy & roadmap: Set vision and priorities across orchestration, triggers, authoring, and observability. Translate customer needs into features and integrations that accelerate Lakeflow Jobs adoption. Drive metrics & observability: Define success metrics for adoption, engagement, and developer efficiency. Use data to guide roadmap decisions and refine the product experience. Collaborate cross-

Role: Point72 is looking for a Fund Flow Strategist to join its Fund Flow Research team. The Fund Flow Group provides best in class flow and positioning indicators to help PMs, analysts, and traders across all investment functions understand their investment backdrop, better assess reward and risk, and identify alpha opportunities. Responsibilities : Create content targeted at discretionary portfolio managers. Refine and advance current product offerings. Assist in daily workflow contributing to internal communications and data production. Contribute to research efforts formalizing and building new models. Work with PMs and analysts to answer questions and identify needs and additional features. Requirements: Undergraduate degree or higher in a technical field. Passion for research, markets, and problem solving. Strong written and verbal communication skills. Strategy, data science, or quant research experience at a financial institution. Experience working with time series and point in time data. Strong programming skills in Python and SQL. Intellectual curiosity, exceptional attention to detail, and the ability to manage multiple projects and deadlines in a fast-paced environment. Commitment to the highest ethical standards.

About Glean: Glean is the Work AI platform that helps everyone work smarter with AI. What began as the industry’s most advanced enterprise search has evolved into a full-scale Work AI ecosystem, powering intelligent Search, an AI Assistant, and scalable AI agents on one secure, open platform. With over 100 enterprise SaaS connectors, flexible LLM choice, and robust APIs, Glean gives organizations the infrastructure to govern, scale, and customize AI across their entire business - without vendor lock-in or costly implementation cycles. At its core, Glean is redefining how enterprises find, use, and act on knowledge. Its Enterprise Graph and Personal Knowledge Graph map the relationships between people, content, and activity, delivering deeply personalized, context-aware responses for every employee. This foundation powers Glean’s agentic capabilities - AI agents that automate real work across teams by accessing the industry’s broadest range of data: enterprise and world, structured and unstructured, historical and real-time. The result: measurable business impact through faster onboarding, hours of productivity gained each week, and smarter, safer decisions at every level. Recognized by Fast Company as one of the World’s Most Innovative Companies (Top 10, 2025), by CNBC’s Disruptor 50, Bloomberg’s AI Startups to Watch (2026), Forbes AI 50, and Gartner’s Tech Innovators in Agentic AI, Glean continues to accelerate its global impact. With customers across 50+ industries and 1,000+ employees in more than 25 countries, we’re helping the world’s largest organizations make every employee AI-fluent, and turning the superintelligent enterprise from concept into reality. If you’re excited to shape how the world works, you’ll help build systems used daily across Microsoft Teams, Zoom, ServiceNow, Zendesk, GitHub, and many more. You'll be deeply embedded where people get things done. You'll ship agentic capabilities on an open, extensible stack, with