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Senior Machine Learning Engineers at Thoughtworks build, maintain and test the architecture and infrastructure for managing machine learning applications. They are involved in supporting and contributing to the design of the end-to-end applications and products. They are responsible for building core capabilities including technical and functional machine learning systems and applications, being the anchor for functional streams of work and are accountable for timely delivery. As a senior machine learning engineer, you will work on the latest tools, frameworks and offerings while also being involved in enabling credible and collaborative problem solving to execute on a strategy. Due to the nature of the projects and specific client security clearance, this role requires the successful candidate to be a Singapore Citizen or PR of Singapore. Job responsibilities You will contribute to design and drive the development of robust scalable architectures and infrastructure for deploying and managing machine learning (ML) applications, ensuring high availability, performance and security You will collaborate with data scientists and engineers to translate business needs into effective and efficient ML systems and applications You will own the development and maintenance of core functionalities within ML applications, including ML pipelines, model training and deployment, and monitoring and evaluation You will drive the functional stream of work by providing technical expertise, handling team discussions and ensuring timely delivery of assigned tasks You will stay ahead of the curve by actively exploring and implementing the latest tools, frameworks and offerings in the ML landscape You will facilitate collaborative problem solving within the team by actively listening, communicating effectively and mentoring other engineers You will contribute to the development and execution of the team's overall ML strategy, aligning technical capabilities with business objectives You wil

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. Senior Director, Quality Engineering – Performance, Scalability & Reliability Location: San Francisco, CA | San Jose, CA Team: Product & Engineering Type: Full-Time About Okta Okta is the World’s Identity Company. We free everyone to safely use any technology—anywhere, on any device or app. Our Workforce and Customer Identity Clouds enable companies to protect the identities of their applicants, employees, and customers, while providing seamless access from any device, anywhere. Thousands of customers, including Adobe, JetBlue, and Farmers Insurance, trust Okta to help them work faster, boost efficiency, and stay secure. Okta’s top priority is to provide a reliable, scalable, and secure platform. We are building a world where anyone can safely use any technology, and we need exceptional leaders to help us achieve this vision. Position Overview As the Senior Director of Performance, Scalability, and Reliability Engineering, you will be responsible for leading the global strategy, architecture, and execution of end-to-end performance testing, capacity planning, and system reliability across all Okta product lines. In this high-impact executive role, you will lead a team of high-performing engineers and managers dedicated to ensuring the Okta Identity Cloud operates at peak efficiency, extreme throughput, and five-nines (99.999%) availability. You will partner closely with Core Engineering, Product Management, Infrastructure, and Si

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 is seeking a Solutions Engineer in Melbourne with expert experience in Cloud Security, IoT Systems, Networking, Linux systems, Security Surveillance and Access Control. This individual will partner directly with their Territory Enterprise Account Executives to expand the Verkada footprint upmarket into Fortune 500 companies. Responsibilities include directly interfacing with customers/partners throughout the sales process, overcoming technical objections, assisting customers in designing deployments with Verkada Products and providing technical assistance to territory Enterprise AE's. The ideal candidate will be highly motivated, able to learn quickly and work independently while making impactful results for the company remotely. This is a full-time remote position; applicants must be located in Melbourne. What You'll

Our Purpose Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we’re helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential. Title and Summary Director, Platform Engineering Who is Mastercard? Mastercard is a global technology company in the payments industry. Our mission is to connect and power an inclusive, digital economy that benefits everyone, everywhere by making transactions safe, simple, smart, and accessible. Using secure data and networks, partnerships, and passion, our innovations and solutions help individuals, financial institutions, governments, and businesses realize their greatest potential. Our decency quotient, or DQ, drives our culture and everything we do inside and outside of our company. With connections across more than 210 countries and territories, we are building a sustainable world that unlocks priceless possibilities for all. Role Summary Director, Platform Engineering At Mastercard, the pace of change across technology, AI, and the nature of work requires that we constantly push the boundaries for the technologies in building and operating infrastructure and applications globally. The Director, Platform Engineering is a critical technology and engineering leadership role within Operations Automation Program accountable for advancing our infrastructure and platform automation strategy through innovation and effective problem-solving. This role focuses on analyzing, coding, and delivering software an

Job Details: Job Description: This position requires candidates to upload a resume in English; you are welcome to upload multiple versions of your resume if you prefer but an English version of your resume will be required to be considered for this position. We are looking for someone who is passionate about working hands-on with both internal and external teams to deliver impactful Fleet and Scale software solutions that are critical to Data Center customers. You will be part of a team responsible for developing Customer Fleet and Scale capabilities that enable high-quality Intel server product launches and improve in-fleet customer experience. The ideal candidate is a quick learner, results-oriented, and comfortable operating in a dynamic environment. As a Cloud Software Development Engineer with uArch expertise, you will play a key role in developing customer fleet health software capabilities and ecosystem. The position focuses on the development, validation, maintenance, and debugging of cloud-scale platform monitoring, telemetry, diagnostics, and fleet screening software used by Intel and hyperscale cloud customers to improve Xeon platform quality, reliability, and deployment readiness. You will work closely with architecture, platform validation, manufacturing, and customer engineering teams throughout the server product lifecycle. The role involves developing customer-consumable software that provides visibility into system state, platform telemetry, hardware health indicators, and Intel Architecture internals to help customers solve in-field and at-scale operational challenges. Responsibilities Develop and maintain screening software capabilities supporting customer fleet health and platform quality initiatives. Design, develop, and optimize telemetry collection, diagnostics,

We are seeking a dedicated and highly skilled Digital MarTech lead to help drive and implement best in class marketing technology platforms and tools to deliver against Citibank’s Consumer Banking vision of generating always on and personalized marketing. The individual in this role will inform, plan, and deliver Marketing’s Technology tools that drive acquisition and engagement of customers & prospects across channels. The job requires a deep understanding of one or more of the following technologies/tools and its corresponding architecture landscape: Content Management platforms (e.g. AEM, genAI tools), Orchestration/Personalization platforms (e.g. Google Ad Manager, Pega, Zeta, Adobe Target, Persado, Stensul, Adobe Experience Platform) and Data Management platforms (e.g. AWS, Snowflake, CDPs). This role is responsible for managing the platform lifecycle, supporting cross-functional digital projects, and ensuring high performance, stability, and seamless user experiences. The product manager will work closely with stakeholders across marketing, analytics, risk, technology, product, and design teams to deliver digital first solutions that align with business objectives and enhance customer engagement. Responsibilities: Platform Ownership: Oversee Google Ad Manager, ensuring it meets business requirements, user needs, and performance expectations. Integrate data and content platform with Commerce Ad platforms (GAM, Live Ramp) to enable onsite and offsite marketing Tech Development: Steer the design, development, testing, deployment, and maintenance of the platforms, including data ingestion, data processing and enablement of real-time audience using Customer Data Platform (CDP) and Adobe Journey Orchestration (AJO) Optimization & Upgrades: Manage ongoing platform optimization, including regular upgrades, feature enhancements, and content performance tuning to achieve a high-performin

Senior Software Engineer - Lab Provisioning & Integration Company: The Boeing Company The Boeing Company is currently seeking a Senior Software Engineer - Lab Provisioning & Integration in Berkeley, MO . You will apply sophisticated engineering principles and deep expertise to architect and deliver highly scalable, secure, and resilient lab environments supporting critical multi-program integration and test activities. You will lead initiatives requiring creativity and ingenuity, influence organizational technical direction, and provide leadership and mentorship in cloud infrastructure, automation, and DevSecOps. This role carries significant responsibility for ensuring technical excellence, delivering innovative solutions to complex challenges, and acting as a primary technical liaison with internal teams and external stakeholders. Position Responsibilities: Advanced Lab Environment Leadership: Apply specialized knowledge and insights to architect, provision, and optimize complex lab/test environments on-premises and across cloud platforms (Azure, AWS) using Infrastructure as Code (Terraform, Ansible). Establish and standardize best practices. Integration Testing Architecture: Lead the design and continuous improvement of enterprise-wide automated integration testing workflows involving multiple program segments, ensuring comprehensive, data-driven feedback and rapid resolution of cross-segment integration issues. Strategic Deployment Pipeline Ownership: Drive innovation in deployment mechanisms and pipelines for physical and virtual systems, ensuring scalability, security, repeatability, and operational excellence aligned with long-term organizational obj

Job Requisition ID # 26WD100721 Engineering Manager Help shape how cities are designed We are looking for an Engineering Manager to grow and develop talent across our organization in our AI-powered architecture design platform. You will spend roughly 70% of your time on product development and 30% on people leadership, managing career growth, removing blockers, and developing individual contributors. You will be working with a group of engineering managers, focusing on the health and growth of our people. As an Engineering Manager you will be the people leader for a group of individual contributors who work on different product teams. You will combine hands-on technical judgment with thoughtful people leadership. You will mentor engineers in their growth, set quality and technical standards, and remove blockers so your engineers can do their best work. You will work alongside your people on systems that combine cloud architecture, performance-sensitive applications, and AI to support complex design and simulation workflows. Your work will enable architects, planners, and developers to discover smarter, more sustainable solutions and gain meaningful insights into their projects. About us We are on a mission to help design better cities. With 90% of future population growth expected in urban areas, and construction responsible for around 40% of global CO₂ emissions, the AEC industry must evolve. Our cloud-based Autodesk Forma platform helps users evaluate design choices based on environmental impact, living quality (sun, daylight, noise), and project feasibility. We started as S

As a member of the HW Infrastructure Storage Strategy team, you will be the bridge between storage infrastructure and the chip design (e.g. NVIDIA GPUs and CPUs) workloads that depend on it. You will focus on going hands-on to understand how storage behavior impacts EDA (Electronic Design Automation) and HPC workload performance in general — and what to do about it. You’ll evaluate next-generation storage technologies, design POCs grounded in real workload profiles, uncover gaps in observability, and drive strategic decisions like data placement during datacenter transitions. This is a rare role where you’ll work at the intersection of storage systems and chip design workflows at a scale few companies reach — petabytes of active data, millions of files per job, and thousands of concurrent users. You’ll develop NVIDIA’s storage strategy and have a direct, measurable impact on engineering velocity. What you'll be doing: Lead storage technology evaluations — design and execute POCs for platforms such as NetApp, VAST, and others, using real EDA workload profiles to benchmark performance, metadata behavior, and compatibility Analyze how storage configurations and architecture choices impact EDA workload runtime in production, and recommend tuning or architectural changes to reduce job execution time Identify gaps in storage telemetry and observability — define what metrics are needed and how to correlate storage behavior with jobs running on the environment Support datacenter lifecycle programs — expansions, technology refreshes, and site exits — by mapping workload placement, identifying required data, and minimizing data replication scope Define storage policies and best practices — data lifecycle, tiering strategies, snapshot/clone workflows (e.g., FlexClone for EDA workspace branching), and capacity planning recommendations Collaborate with IT, EDA tool teams, EDA operations, and

The Security Incident Response Team (SIRT) plays a vital role in keeping Datadog safe from cybersecurity threats, defending the organization against threat actors, and maintaining the trust of our customers by ensuring their data remains protected. In this role, you will work closely with teams across Datadog to identify, triage, and respond to a wide range of threats, ensuring that we can contain any incidents as quickly as possible. You will also contribute to the tools and systems that make us more effective in our mission, and help ensure we have cross-functional learning from incidents to improve our defensive posture going forward. At Datadog, we place value in our office culture - the relationships and collaboration it builds, and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You’ll Do: Partner with our Cyber Threat Intelligence and Detection Engineering teams to identify threats to Datadog and ensure we have appropriate, accurate, high-signal detections for those threats. Triage escalated alerts to determine whether a security incident is occurring or may occur imminently. Respond to security incidents, whether as an incident commander or as an incident responder Make us more efficient through building tools and automations that eliminate repetitive processes Help us improve our overall security posture through post-incident reviews, tabletop and purple team exercises, and process/runbook improvements. Participate in a light on-call rotation. Who You Are: You have at least 5 years of experience in security incident response, threat hunting, security operations, cloud security, or other operational security domains. You’ve worked with at least one public cloud platform (AWS, GCP, or Azure) and cloud-native technologies like Kubernetes, Docker, or Terraform. You have a strong understanding of cloud-native threat actor TTPs and corresponding defensive contr

The Role As a Senior Customer Success Manager, you are a highly experienced advisor helping customers navigate their most complex journeys on MongoDB. You’ll be responsible for maximizing customer lifetime value and success for a portfolio of Enterprise (G2000) accounts, acting as a lead strategic connector between your customers and cross-functional resources to achieve high-stakes business goals. You’ll drive customer retention, revenue realization, and long-term advocacy while mentoring team members to elevate the organization's collective impact. You’ll build deep relationships with senior stakeholders, understand intricate technical environments inside and out, and navigate global account teams to deliver measurable impact in high-pressure scenarios. Key Responsibilities Customer Advisory Proactively identify and mitigate risks in accounts with significant technical complexity by advising on advanced operational strategies and best practices. Deliver cross-disciplinary solutions to critical customer challenges, accelerating time-to-value and guiding to achieve their business goals through their MongoDB deployments Conduct comprehensive customer business reviews for Enterprise accounts, analyzing technical health and risk while translating insights into business-critical outcomes. Partner with senior technical and business leaders to align on objectives and champion mutual success plans that foster long-term advocacy Account & Portfolio Management Drive cross-functional development of account strategy and take ownership of elements that drive customer maturity, lifetime value, retention, and revenue realization. Proactively manage a diverse portfolio of Enterprise customers across various stages of the journey, creating and executing strategies to maximize value realization, advocacy, and long-term success Track and report progress against key business outcomes, demonstrate control of the forecast by providing informed predictions to senior leadership for bu

REQ ID: FEQ227R147 Location: Germany (Remote/Hybrid) - will require travel across Europe Recruiter: Dina Hussain About the Role We are looking for a Lead Solution Architect focused on Generative AI to support our EMEA Emerging Digital Natives and Startups business unit — one of the fastest-moving, most technically ambitious patches in EMEA. Our customers are digital-native and cloud-native companies who build on the frontier: they adopt GenAI early, scale fast, and expect their technical partners to be as sharp as their own engineers. You will be the go-to expert our Account Teams and customers turn to when a GenAI or LLM use case needs to move from an ambitious idea to a production-grade reality across our high-growth accounts. This is a highly technical, customer-facing individual contributor role for someone who lives at the frontier of applied GenAI. You will shape architectures, prove out the hard problems, challenge and influence customer roadmaps, and raise the GenAI capability of the entire EMEA Emerging DNB field organisation. What You'll Do Serve as the deep technical authority on Generative AI, LLMs, and applied machine learning for the EMEA Emerging DNB business unit, supporting the most strategic and complex customer engagements across our digital-native and born-in-the-cloud accounts. Partner with our EMEA Emerging DNB Solutions Architects, Solutions Engineers, and Account teams to scope, design, and de-risk GenAI use cases — from retrieval-augmented generation and agentic systems to fine-tuning and evaluation. Build hands-on proofs of concept and reference implementations that operationalise large-scale LLM and deep learning workloads on Databricks (Mosaic AI, MLflow, Model Serving, Vector Search, Unity Catalog governance), tuned to the fast iteration cycles Emerging DNB customers expect. Lead fine-tuning and model-customisation engagements on open LLMs (e.g., Llama-family models), including judge-based and label-efficient evaluation approaches for do

REQ ID: FEQ227R147 Location: France (Remote/Hybrid) - will require travel across Europe Recruiter: Dina Hussain About the Role We are looking for a Lead Solution Architect focused on Generative AI to support our EMEA Emerging Digital Natives and Startups business unit — one of the fastest-moving, most technically ambitious patches in EMEA. Our customers are digital-native and cloud-native companies who build on the frontier: they adopt GenAI early, scale fast, and expect their technical partners to be as sharp as their own engineers. You will be the go-to expert our Account Teams and customers turn to when a GenAI or LLM use case needs to move from an ambitious idea to a production-grade reality across our high-growth accounts. This is a highly technical, customer-facing individual contributor role for someone who lives at the frontier of applied GenAI. You will shape architectures, prove out the hard problems, challenge and influence customer roadmaps, and raise the GenAI capability of the entire EMEA Emerging DNB field organisation. What You'll Do Serve as the deep technical authority on Generative AI, LLMs, and applied machine learning for the EMEA Emerging DNB business unit, supporting the most strategic and complex customer engagements across our digital-native and born-in-the-cloud accounts. Partner with our EMEA Emerging DNB Solutions Architects, Solutions Engineers, and Account teams to scope, design, and de-risk GenAI use cases — from retrieval-augmented generation and agentic systems to fine-tuning and evaluation. Build hands-on proofs of concept and reference implementations that operationalise large-scale LLM and deep learning workloads on Databricks (Mosaic AI, MLflow, Model Serving, Vector Search, Unity Catalog governance), tuned to the fast iteration cycles Emerging DNB customers expect. Lead fine-tuning and model-customisation engagements on open LLMs (e.g., Llama-family models), including judge-based and label-efficient evaluation approaches for dom

REQ ID: FEQ227R147 Location: Sweden (Remote/Hybrid) - will require travel across Europe Recruiter: Dina Hussain About the Role We are looking for a Lead Solution Architect focused on Generative AI to support our EMEA Emerging Digital Natives and Startups business unit — one of the fastest-moving, most technically ambitious patches in EMEA. Our customers are digital-native and cloud-native companies who build on the frontier: they adopt GenAI early, scale fast, and expect their technical partners to be as sharp as their own engineers. You will be the go-to expert our Account Teams and customers turn to when a GenAI or LLM use case needs to move from an ambitious idea to a production-grade reality across our high-growth accounts. This is a highly technical, customer-facing individual contributor role for someone who lives at the frontier of applied GenAI. You will shape architectures, prove out the hard problems, challenge and influence customer roadmaps, and raise the GenAI capability of the entire EMEA Emerging DNB field organisation. What You'll Do Serve as the deep technical authority on Generative AI, LLMs, and applied machine learning for the EMEA Emerging DNB business unit, supporting the most strategic and complex customer engagements across our digital-native and born-in-the-cloud accounts. Partner with our EMEA Emerging DNB Solutions Architects, Solutions Engineers, and Account teams to scope, design, and de-risk GenAI use cases — from retrieval-augmented generation and agentic systems to fine-tuning and evaluation. Build hands-on proofs of concept and reference implementations that operationalise large-scale LLM and deep learning workloads on Databricks (Mosaic AI, MLflow, Model Serving, Vector Search, Unity Catalog governance), tuned to the fast iteration cycles Emerging DNB customers expect. Lead fine-tuning and model-customisation engagements on open LLMs (e.g., Llama-family models), including judge-based and label-efficient evaluation approaches for dom

REQ ID: FEQ227R147 Location: Netherlands (Remote/Hybrid) - will require travel across Europe Recruiter: Dina Hussain About the Role We are looking for a Lead Solution Architect focused on Generative AI to support our EMEA Emerging Digital Natives and Startups business unit — one of the fastest-moving, most technically ambitious patches in EMEA. Our customers are digital-native and cloud-native companies who build on the frontier: they adopt GenAI early, scale fast, and expect their technical partners to be as sharp as their own engineers. You will be the go-to expert our Account Teams and customers turn to when a GenAI or LLM use case needs to move from an ambitious idea to a production-grade reality across our high-growth accounts. This is a highly technical, customer-facing individual contributor role for someone who lives at the frontier of applied GenAI. You will shape architectures, prove out the hard problems, challenge and influence customer roadmaps, and raise the GenAI capability of the entire EMEA Emerging DNB field organisation. What You'll Do Serve as the deep technical authority on Generative AI, LLMs, and applied machine learning for the EMEA Emerging DNB business unit, supporting the most strategic and complex customer engagements across our digital-native and born-in-the-cloud accounts. Partner with our EMEA Emerging DNB Solutions Architects, Solutions Engineers, and Account teams to scope, design, and de-risk GenAI use cases — from retrieval-augmented generation and agentic systems to fine-tuning and evaluation. Build hands-on proofs of concept and reference implementations that operationalise large-scale LLM and deep learning workloads on Databricks (Mosaic AI, MLflow, Model Serving, Vector Search, Unity Catalog governance), tuned to the fast iteration cycles Emerging DNB customers expect. Lead fine-tuning and model-customisation engagements on open LLMs (e.g., Llama-family models), including judge-based and label-efficient evaluation approaches fo