Machine Learning Engineer (GoLang)

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 Okta Privileged Access Management (PAM) is an identity-centric approach to a common and critical privileged access use case. Our elegant Zero Trust architecture is purpose-built for the modern cloud and helps customers solve challenging security and operations pain points at scale. We are looking for a software engineer to join our fast-growing team with a focus on scalability, reliability, and enhancing the core building blocks of the product. In this role you will: Be deeply involved in evolving the core architecture of PAM. Work in our product development teams to build scalable, composable components of our platform. Be responsible for designing and implementing scalable architecture patterns. Delight our customers by providing world class UX using our React-based design system Design and build APIs that customers rely on for access to production infrastructure. Work on backend components written in Go and frontend components written in React. You might be a good fit if you: Have 3-5 years of software development experience with a background in Golang or similar programming languages. Proficient in React or similar front-end UI stacks. Experienced working with relational databases like PostgreSQL or similar RDBMS technologies. have the ability to complete a feature end to end from designing database models to backend APIs and frontend UI components. Experienced working with any cloud provider such as AWS, GCP or Azure. Thrive in a collaborativ

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 Streaming Foundations team builds services and operates data pipeline infrastructure to support event streaming, messaging, and analytics use cases. We are looking for a Software Engineer who is passionate about distributed systems, platform engineering, and solving data-intensive problems at scale. In this high-impact role, you will get to work with engineers throughout the organization to build foundational infrastructure that allows Auth0 to scale for years to come. What you’ll be doing Help set the technical direction for the team and influence the engineering roadmap for the Platform’s streaming capabilities Design and lead the implementation of our most complex and critical systems for data-intensive use cases. Research and champion new technologies and architectural patterns to solve strategic challenges and scale the platform. Lead and influence cross-functional initiatives, ensuring technical alignment and successful execution across multiple teams. Improve the operational posture of our systems by designing for observability, reliability, and scalability, and by mentoring others in operational best practices. Coach and mentor senior engineers and act as a technical leader across the engineering organization. Collaborate with different stakeholders like product teams whenever needed. What you’ll bring to our teams 7+ years of software development experience in a fast-paced, agile environment Experience working with Golang or Java is preferred H

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. Job Description Okta’s Auth0 is an easy to implement, adaptable authentication and authorization platform. We make everyone’s login experience awesome. If you are a problem solver who wants to make this login experience even better, then look no further - Okta Auth0 B2C Authentication domain is where you want to be. Our domain’s mission is to provide a simple, secure, standards-compliant and delightful authentication experience for both end users and developers. We work with NodeJS, React, golang, Swift, Java / Kotlin, Postgres/MongoDB databases and our services run on both AWS and Azure. Our tech stack continues to evolve and expand to new technologies and trends. We are proponents of using the right tools for the job. We are looking for an engineer who leverages AI coding assistants (e.g., GitHub Copilot, Google Gemini, Claude) to accelerate the software development lifecycle without compromising security. You should be proficient in using LLMs for rapid prototyping, boilerplate generation, and complex refactoring , effectively cutting down development time. Crucially, you must possess the judgment to audit, debug, and secure AI-generated code, ensuring it meets our strict authentication standards. You will use AI not just to write code, but to generate comprehensive unit tests, document systems, and simulate edge-case scenarios in our auth flows. As a member of the Native Apps team you will: Be a part of fast paced, agile team comprising of engineers, a

Staff Software Engineer - Testing & Automation Exceptional software engineering is challenging. Amplifying it to ensure that multiple teams can concurrently create and manage a vast, intricate product escalates the complexity. As a Staff Engineer within the Verification Platform team at Sumo Logic, you will drive the implementation and optimization for our verification platform as well as the modernization of our CI/CD pipelines. Your mission is to develop and sustain automated tooling for all testing, verification, and functional requirements, leveraging AI reasoning and machine learning models to predict and prevent delivery issues, while integrating advanced security validation and non-functional requirements into our delivery lifecycle. You will contribute significantly to establishing automated delivery pipelines, empowering autonomous teams to create independently deployable services, and progressing Sumo Logic’s internal Platform-as-a-Service. This role sits at the intersection of Platform Engineering, Quality Engineering, DevSecOps, and Developer Productivity, helping teams deliver secure, reliable, and independently deployable services at scale. Responsibilities Strategy & Leadership: Drive technical direction and design for a modern Quality Engineering platform, driving the adoption of AI reasoning for enhanced automation of all testing, verification, and functional requirements. Pipeline Modernization: Lead the modernization of CI/CD pipelines to include automated security validation, compliance checks, and other critical non-functional requirements, with a focus on integrating AI/ML for intelligent pipeline optimization and risk prediction. Framework Ownership: Own the delivery pipeline and release automation framework for all Sumo services, ensuring improvements in developer productivity, deployment frequency, and release reliability. Cross-Team Collaboration: Educate and collaborate with teams during design and development phases to ensur

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, Driver, Marketplace, 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 petabyte-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. The Fulfillment group, within the Marketplace at Lyft, is responsible for determining what inventory can be reliably offered for a given rider session and fulfilling rider requests. The group comprises several sub-teams that generate feasible offers for riders, match rider requests with drivers, and maintain a distributed state machine to track rides and drivers from request through completion. We are seeking a Machine Learning Engineer to join the Fulfillment team and lead the design, development, and deployment of state-of-the-art machine learning 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 machine learning and data science. Responsibilities: Design, build, and deploy machine learning models for real-time applications, including translating state-of-the-art research into production-ready solutions Design and implement feature pipelines, model training workflows, and serving infrastructure using Lyft's ML platform Evaluate ML system performance against business KPIs, run experiments, and drive continuous model improvement

Machine Learning Engineer We’re looking for a Machine Learning Engineer with deep expertise in computer vision and biometrics to lead the design and scaling of face recognition systems in production. You’ll build and train models, and own ML systems end-to-end on AWS. The final job level for this role will be determined following the interview process. What You’ll Do Lead the design and development of computer vision systems for biometrics (face attributes, detection, quality, and recognition) Rigorous fairness analysis and benchmarking of biometric models across various datasets and operating conditions. Architect, train, and optimize models using PyTorch, Tensorflow, and/or JAX Own and evolve end-to-end ML pipelines, from data ingestion to deployment. Design automated pipelines (Airflow) for data ingestion and cleaning. You will be responsible for curating balanced training sets and generating synthetic data to address both quality and diversity gaps. Production Engineering: Own the path to production. Optimize models for low-latency inference (quantization, distillation, TensorRT/ONNX) and manage deployment on AWS. Mentor ML engineers, conduct code/design reviews, and drive technical best practices across the Computer Vision team. What We’re Looking For Experience: Multiple years of industry experience in Machine Learning, with at least 3 years dedicated to Biometrics or Face Analysis. Deep expertise in computer vision and biometrics, especially face recognition. Fairness & Ethics: You understand the sources of algorithmic bias in Computer Vision and have practical experience measuring and mitigating disparate impact. Strong Engineering: Expert proficiency in Python (both machine learning and vision libraries such as Pillow, OpenCV, PyTorch, etc). You write clean, modular, production-ready code. Systems Architecture: Experience designing end-to-end ML pipelines (Data to Train to Deploy) and working with workflow orchestrators like Airflow. Cloud Native: