Python Developer Jobs

Location Details: Remote, India 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 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... GoDaddy’s Product Security team is looking for a Security Engineer who is passionate about helping build secure products and services used by millions of customers worldwide. In this role, you will work closely with engineering and platform teams to identify security risks, improve security practices, and help embed security throughout the software development lifecycle. You will have the opportunity to learn from experienced security professionals while contributing to initiatives that improve the security and resilience of our products, platforms, and cloud environments. The ideal candidate is curious, hands-on, eager to learn, takes ownership of their work, and excited to solve security challenges at scale! What you'll get to do... Identify, assess, and help remediate security risks across applications, infrastructure, cloud environments, and AI-enabled services Partner with engineering and platform teams to design, implement, and improve security controls throughout the software development lifecycle Conduct security reviews, threat modelling, and risk assessments to help build secure, resilient, and scalable systems Develop and enhance automation, tooling, and processes that strengthen security coverage, improve detection and response capabilities, and increase operational efficiency Investigate security findings, stay informed on emerging threats and technologies, and contribute to a culture of security awareness and continuous learning Your experience should include... 2+ yea

About Us Paytm is India’s leading digital payments and financial services company, which is focused on driving consumers and merchants to its platform by offering them a variety of payment use cases.aytm offers acquiring devices like Soundbox, EDC, QR and Payment Gateway where payment aggregation is done through PPI and also other banks’ financial instruments. To further enhance merchants’ business, Paytm offers merchants commerce services through advertising and Paytm Mini app store. Operating on this platform leverage, the company then offers credit services such as merchant loans, personal loans and BNPL, sourced by its financial partners. About the role: Evangelize and demonstrate the value and impact of analytics for informed business decision making by developing and deploying analytical solutions and providing data driven insights to business stakeholders to understand and solve for various lending business nuances. The Credit Risk Analyst will be responsible for monitoring , analysing and optimising lending portfolios across consumer / merchant lending products. This includes overseeing portfolio health , developing / refining risk strategies and supporting business growth through risk adjusted decision making. Key Responsibilities : - Portfolio Monitoring & Analytics - Risk Strategy & Policy Design - Stress Testing & Risk Containment - Loss forecasting & scenario planning - Product & Growth Partnership - Collections Interface / Strategy - Compliance & Bureau Management Requirements: - 5 to 8 yrs in portfolio risk management function in Fintech/ Banks/ NBFC - Hands on experience in SQL, Python, R, Pyspark - Good understanding of Bureau data, Alternate Data, Scorecards, Digital Lending API's etc - Ability to translate data into clear insights and recommendations - Familiarity with BI tools like Tableau, Looker , Metabase etc - Understanding of machine learning models in credit risk - Strong problem solving and stakeholder management skills

We are looking for an experienced Staff Software Engineer with a strong background in building software frameworks, LLM eval frameworks and team leadership. You will lead a talented team building a complex product suite using a modern stack. The ideal candidate is a hands-on technical leader who can drive architectural decisions, mentor engineers, and collaborate closely with product management to deliver a product that solves our customers' most challenging modernization validations problems, ensuring that new applications have the same functionality and performance as their legacy counterparts. This role will be based in our India office in Gurgaon and offers a hybrid working model. The ideal candidate for this role will have 8+ years of commercial software development experience with at least one JVM language such as Java, preferably using the Spring ecosystem and paired with strong Python experience 2+ years of experience leading, coaching, and mentoring a team of software engineers to achieve high-impact results Solid experience in software architecture and development Familiarity with evaluation frameworks (such as DeepEval, Ragas, and Promptfoo) and harnesses, alongside benchmark datasets, scoring/grading approaches, and LLM-as-a-judge methodologies Experience in application/database modernization with proven ability to design and implement frameworks that ensure database state equivalence across different implementations Must understand change data capture, event-driven database interception (MongoDB listeners, RDBMS triggers), and state comparison algorithms with pattern-based exclusions Extensive experience with relational and document data modeling and hands-on experience with at least one SQL database (Postgres, MySQL, etc) and at least one document database (e.g. MongoDB) Good understanding of algorithms, data structures and their time and space complexity Curiosity, a positive attitude, and a drive to continue learning Excellent verbal and written comm

About Stitch Fix, Inc. Stitch Fix (NASDAQ: SFIX) Stitch Fix is redefining retail by combining human creativity with advanced data science and Generative AI. As we build the future of personalized shopping, we’re equally committed to building yours. We believe in investing in our team as much as our technology. Join us to be a trendsetter in the industry and help us redefine what’s possible for our clients, while we help you reach your full potential. About the Role At Stitch Fix, we are at the forefront of innovation, creating cutting-edge solutions that blend fashion, technology, and data science. Our data science team combines machine learning with expert human judgment to generate innovative recommendations and insights that transform the way our clients discover what they love. We believe in a curiosity-driven data science culture where members are empowered to deliver impact through end-to-end model development. The diversity of the problems that we work on and the data-rich environment of our business make it possible, even essential, to bring the tools of multiple disciplines to bear on our hardest problems. We are looking for an experienced Styling Algorithms Team Manager to lead a group of talented machine learning engineers and data scientists. In this role, you will shape the future of fashion technology by driving the development and deployment of our styling algorithms, which empower our human stylists to delight clients by nailing their fit and style. This includes ML-, AI-, and product-driven feature curation and testing for our proprietary styling platform, as well as client-facing AI personalization experiences, such as Stitch Fix Vision, our virtual try-on. Responsibilities: Champion bold AI and ML interventions to improve our styling experiences, enabling our stylists to have a multiplicative impact on their client connection points. Likewise, actively shape the product roadmap for direct client-facing styling experiences, expand

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 Bikes & Scooters team is developing the future of micro-mobility and we are looking for a solid, experienced Software Engineer to join our Stations Software Platform team to work on helping us transition our customers to our latest generation platform and to make the platform evolve in a solution that can be brought to multiple different markets and business models. Technical interviews and interactions with the other offices in the company will be in English; however, the working environment in Montreal is bilingual. Responsibilities: Help define the roadmap and architecture based on technology and business needs 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: BSc/MSc in Computer Engineering, Computer Science, related field or relevant work experience 5+ years of software engineering industry experience Experience with object-oriented programming Experience in distributed systems Experience with Java and/or Python, familiarity with Scala is a plus Experience working with databases, relational or NoSQL Experience writing clear, scalable and clear design documentation Experience designing, building and improving a set of team owned components Must have a track record of professional excellence Benefits: Extend

Who We Are Nuro believes self-driving vehicles are the most immediate and profound opportunity for AI to drive positive change in the physical world. Safer streets, more time for what matters, and easier access to the world around us, that’s why we’re building a universal autonomy platform: self-driving for all roads and all rides. Founded in 2016, Nuro is a physical AI company developing Level 4 autonomous driving technology for a wide range of vehicles, use cases, and markets. Powered by the Nuro Driver™, our universal autonomy platform enables the global mobility ecosystem to deploy autonomy at scale, from robotaxis and logistics fleets to personal vehicles. With years of real-world deployment experience and a flexible, partner-led business model, Nuro is working toward a future where millions of autonomous vehicles powered by our technology help make everyday life safer, easier, and more connected. Nuro has raised over $2B in capital from Uber, NVIDIA, Google, Softbank, Fidelity, T. Rowe Price, and other leading investors. About the Work Lead system-level requirements definition, architecture design, integration strategy, and validation in one of the platform areas — autonomy sensors, AV compute, motion control, pose/localization, or end-to-end latency. Characterize and quantify system performance for that area: define nominal targets, minimum performance, and acceptance criteria across all ODDs, and defend those numbers with data rather than convention. Recommend operating constraints for current and future ODDs on different vehicle platforms — for example trajectory constraints for a given virtual driver, or sensor performance envelopes. Define and quantify test coverage for your area, including the realism and relevance of proposed tests across simulation, SIL/HIL, closed course, and on-road. Partner with software teams to define interfaces, performance metrics, failure modes, and validation strategies; validate platform modules against ground truth whe

About Us: Paytm is India's leading mobile payments and financial services distribution company. Pioneer of the mobile QR payments revolution in India, Paytm builds technologies that help small businesses with payments and commerce. Paytm’s mission is to serve half a billion Indians and bring them to the mainstream economy with the help of technology. Key Responsibilities: Collection Strategy & Analytics - Develop strategies for all collections related activities and ensure that the processes are followed as planned Analyzing the data and Implementing different collection strategies with Data Science Regular improvement in processes & collection strategies. A/B testing, data analysis and iterations. Develop and implement advanced analytics approaches including statistical modelling Analyze big data (structured and unstructured) and understand trends to provide actionable insights that impact business bottom line. Break down the Loss forecasts into collections roll rates and recovery rates Track Account-to-Collection Ratios (ACR) by bucket to optimize collections performance Segmentation analysis has to be conducted using analytical tools and strategies for each segment have to be deployed across buckets. Devise Champion Challenger programs showing Cost Vs Benefit analysis driving higher resolution rates across products and buckets Analyzing data: Performing quantitative and qualitative analysis on accounts. Developing strategies: Developing collection strategies based on insights from stakeholders. Implementing strategies: Working with the collection strategy support unit to implement and control the execution of strategies. Improving processes: Automating processes, data, and models to improve productivity. Forecasting losses: Increasing the accuracy of loss-forecasting strategies. Segmenting customers: Developing more effective contact strategies by segmenting customers, including behavioral segmentation. Meeting regulatory requirements: Applying individualized c

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. The Trust & Safety function at Lyft is dedicated to keeping every Lyft ride safe for both riders and drivers. We build and maintain the tools, features, and systems that deter bad actors, protect vulnerable populations, and reinforce trust across the platform. As an Backend Engineer working on Trust & Safety, you'll work at the intersection of product, design, engineering, and policy to ship high-impact safety features to millions of users. Responsibilities: Drive high-impact projects and innovate new solutions to provide the best user experience. Work closely with cross-functional teams and partner teams to develop solutions based on technology and business needs, and advance team’s goals and priorities Independently lead features from idea to positive execution and launch Unblock, support and communicate with internal partners to achieve results Write well-crafted, well-tested, readable, maintainable code Utilize your expertise in Python, Golang, AWS to deliver robust and scalable solutions Participate in code reviews to ensure code quality and distribute knowledge, as well as on call rotations Share your knowledge by giving brown bags, tech talks, and promoting appropriate tech and engineering best practices Experience: BS/MS or equivalent in Computer Engineering, Computer Science, or related field or relevant work experience 3+ years of software engineering industry experience Extensive experience in object oriented programming, ideally in GoLang or Python Experience in backend software development of distributed systems and concurrency Strong oral and written communication skills, and ability to collaborate with and influence cross-functional partners Benefits: Extended health and dental coverage options, along with life insurance and disability benefits Mental health benefits Family bui

Biohub is the first large-scale initiative bringing frontier AI models, massive compute, and frontier experimental capabilities under one roof. We're building a general-purpose system to accelerate scientific discovery, integrating frontier AI models, biological foundation models, and lab capabilities, with the ultimate goal of curing disease. Our technology powers scientists around the world, translating AI capabilities into tools that accelerate research everywhere. The Team Our immune cell reprogramming team integrates foundational research on immunology and disease biology with AI-modeling to develop engineered cells that harness our own immune system to detect and treat early signs of age-related diseases, like cancer, Alzheimer’s, and Parkinson’s. These technologies will enable precise, context-dependent therapeutic responses only when and where it is needed. You can learn more about our work here . Our work brings together three powerhouse universities - Columbia University, The Rockefeller University, and Yale University - into a single collaborative technology and discovery engine. Our Vision Pursue large scientific challenges that cannot be pursued in conventional environments Enable individual investigators to pursue their riskiest and most innovative ideas Facilitate research by scientists and clinicians at our home institutions and beyond We are a team of passionate individuals powered by technology, guided by scientific research, and driven by collaboration, working toward a mission to cure or prevent all disease. The Opportunity Biohub NY is seeking an accomplished computational biologist experienced in machine learning and transcriptomic data analyses to join our interdisciplinary team. Within the Biohub NY “Immune Cell Re-Programming” group, this role requires experience in research settings, a background in biology, and a proven ability to design, evaluate, and publish innovative computational methodologies that leverage machine learnin

Flight Simulation Software Engineers (Associate, Experienced, and Senior) Company: The Boeing Company The Boeing Company is currently seeking Flight Simulation Software Engineers (Associate, Experienced, and Senior) to join the Flight Simulation Labs team located in Berkeley, MO . This position will focus on supporting the Boeing Defense, Space & Security (BDS) business organization. **Our teams are currently hiring for a broad range of experience levels including; Associate, Experienced, and Senior Level Software Engineers. Our Air Dominance software engineers design, develop, and demonstrate avionics solutions for the platforms we build and upgrade. Your efforts will assist in integration of innovative technologies to maintain our platform’s dominance over the battlefield for many decades to come. Additionally, our software engineers support the Flight Simulation products associated with our platforms. The roles will involve software development for tools that support simulation infrastructure across Flight Simulation Labs. Selected candidates will be aligned to a statement of work that best suits their interests and skillset, some of which could include: Creating core simulation infrastructure to serve as a jumping-off point for programs developing flight simulation capabilities Developing tools to simulate, monitor, and capture messages between subsystems in a lab environment Modeling various aircraft capabilities, including the ability to run constructive scenarios in a testing environment Position Responsibilities: Develops, documents and maintains architecture, requirements, algorithms, interfaces and designs for softwa

Synthesia is the world’s leading AI video platform for business, used by over 90% of the Fortune 100. Founded in 2017, the company is headquartered in London, with offices and teams across Europe and the US. As AI continues to shape the way we live and work, Synthesia develops products to enhance visual communication and enterprise skill development, helping people work better and stay at the center of successful organizations. Following our recent Series E funding round, where we raised $200 million, our valuation stands at $4 billion. Our total funding exceeds $530 million from premier investors including Accel, NVentures (Nvidia's VC arm), Kleiner Perkins, GV, and Evantic Capital, alongside the founders and operators of Stripe, Datadog, Miro, and Webflow. About the role You will work on core enterprise platform systems, focusing on services that ensure Synthesia is secure, reliable, and scalable for our largest customers. You will contribute to our new suite of APIs that will unlock our market leading Avatar technology to be utilised by external creative tools. We are an AI native company and use the most powerful assistant tools on a daily basis to increase our speed of development, automate repetitive tasks and widen the scope of what the team can worked on. This includes Claude and Cursor. You will have ownership of projects that span months and multiple teams, requiring you to break down complex, ambiguous problems into clear steps that can be delivered and validated iteratively. Engineers within Synthesia are empowered to contribute heavily to product discussions and build with both user and business considerations in mind. Impact is key to everything we do here. You will work closely with product, security, legal, and infrastructure partners, and will be expected to translate business and regulatory requirements into scalable technical solutions. You will evaluate your work through system health and reliability metrics, leveraging observability and monitori

We are looking for a Senior System Software Engineer, Software Defined Networking to design, build, and operate highly performant and scalable SDN solutions for NVIDIA's AI Clouds hosting GPU-accelerated workloads — including hyperscale multi-node training, inference, cloud gaming, and cloud functions. This role spans the full lifecycle of our SDN stack — from designing and developing new control and data plane software to ensuring operational excellence in production through reliability engineering, CI/CD, observability, and incident response. What you'll be doing: Design and develop next-generation multi-tenant cloud SDN control and data plane software (OVS, OVN, OpenFlow) Build Infrastructure-as-a-Service virtual network orchestration and services using gRPC and REST to support tenant workload security and performance SLAs for BMaaS, VMaaS, and Kubernetes Drive upstream contributions to OVN-Kubernetes and related open-source projects Develop software for network observability — monitoring, telemetry, intelligent metering, and performance analysis Operate and support OVS-OVN based SDN solutions in large-scale NVIDIA AI Cloud environments Own end-to-end observability for the SDN stack — build and maintain monitoring, alerting, distributed tracing, and dashboarding to ensure real-time insight into network health, performance, and tenant SLAs Design, enhance, and maintain CI/CD pipelines (GitLab) across Linux host networking, OVS, OVN, and Kubernetes CNIs Implement GitOps approaches or related experience for secure, seamless integration with cloud infrastructure Drive reliability through incident management, resource monitoring, and performance tuning<

About the Role Adobe is seeking a Machine Learning Engineer to join the Adobe Genuine Engineering team. This group protects Adobe's ecosystem from fraud, abuse, and misuse using intelligent systems worldwide. In this position, you will build and develop machine learning models from scratch, including custom transformer-based frameworks, to identify fraudulent actions, stop account sharing, and protect the experience of hundreds of millions of users. You will manage the entire model lifecycle: raw behavioral data and feature engineering, architecture development, large-scale GPU training, deployment, and monitoring. The team is actively building in-house behavioral foundation models that learn identity-preserving representations from long sequences of user activity. This is a role for an engineer who wants to own deep learning systems end-to-end — not consume pre-built ones. Key Responsibilities Build and train deep learning models from scratch, including custom transformer and attention-based architectures for long behavioral event sequences. Own the full training stack: event tokenization, temporal and positional embeddings, self-supervised pretraining (e.g., masked modeling, contrastive learning), and downstream fine-tuning. Train large models efficiently on GPU infrastructure using mixed-precision training, gradient accumulation/checkpointing, efficient attention, and distributed strategies (DDP, FSDP, or equivalent). Build and optimize feature pipelines on Databricks and Spark, transforming raw behavioral events into high-quality model inputs. Translate prototypes into production ML systems — scalable, reliable, and observable — and drive inference performance through architectural and serving-side optimization. Contribute to MLOps practices: experiment tracking, model versioning, CI/CD, automated retraining, and

About the Role Adobe is seeking a Machine Learning Engineer to join the Adobe Genuine Engineering team. This group protects Adobe's ecosystem from fraud, abuse, and misuse using intelligent systems worldwide. In this position, you will build and develop machine learning models from scratch, including custom transformer-based frameworks, to identify fraudulent actions, stop account sharing, and protect the experience of hundreds of millions of users. You will manage the entire model lifecycle: raw behavioral data and feature engineering, architecture development, large-scale GPU training, deployment, and monitoring. The team is actively building in-house behavioral foundation models that learn identity-preserving representations from long sequences of user activity. This is a role for an engineer who wants to own deep learning systems end-to-end — not consume pre-built ones. Key Responsibilities Build and train deep learning models from scratch, including custom transformer and attention-based architectures for long behavioral event sequences. Own the full training stack: event tokenization, temporal and positional embeddings, self-supervised pretraining (e.g., masked modeling, contrastive learning), and downstream fine-tuning. Train large models efficiently on GPU infrastructure using mixed-precision training, gradient accumulation/checkpointing, efficient attention, and distributed strategies (DDP, FSDP, or equivalent). Build and optimize feature pipelines on Databricks and Spark, transforming raw behavioral events into high-quality model inputs. Translate prototypes into production ML systems — scalable, reliable, and observable — and drive inference performance through architectural and serving-side optimization. Contribute to MLOps practices: experiment tracking, model versioning, CI/CD, automated retraining, and

About the Role Adobe is seeking a Machine Learning Engineer to join the Adobe Genuine Engineering team. This group protects Adobe's ecosystem from fraud, abuse, and misuse using intelligent systems worldwide. In this position, you will build and develop machine learning models from scratch, including custom transformer-based frameworks, to identify fraudulent actions, stop account sharing, and protect the experience of hundreds of millions of users. You will manage the entire model lifecycle: raw behavioral data and feature engineering, architecture development, large-scale GPU training, deployment, and monitoring. The team is actively building in-house behavioral foundation models that learn identity-preserving representations from long sequences of user activity. This is a role for an engineer who wants to own deep learning systems end-to-end — not consume pre-built ones. Key Responsibilities Build and train deep learning models from scratch, including custom transformer and attention-based architectures for long behavioral event sequences. Own the full training stack: event tokenization, temporal and positional embeddings, self-supervised pretraining (e.g., masked modeling, contrastive learning), and downstream fine-tuning. Train large models efficiently on GPU infrastructure using mixed-precision training, gradient accumulation/checkpointing, efficient attention, and distributed strategies (DDP, FSDP, or equivalent). Build and optimize feature pipelines on Databricks and Spark, transforming raw behavioral events into high-quality model inputs. Translate prototypes into production ML systems — scalable, reliable, and observable — and drive inference performance through architectural and serving-side optimization. Contribute to MLOps practices: experiment tracking, model versioning, CI/CD, automated retraining, and