Embedded AI/ML Developer

About Ramp Ramp is building the smart infrastructure for finance teams, embedded in the transaction flow of every dollar a business spends. We automate how over $200B in annualized spend flows in and out of 70,000+ companies: authorizing payments, flagging risk, categorizing spend, and closing books. The problems are high-stakes, data-dense, and unforgiving. We hire people with high agency and high urgency. We look for slope over intercept. We care less about where you trained and more about what you’ve built. At Ramp, everyone is a builder who owns problems end to end and makes consequential decisions that shape the outcome. The median Ramp customer saves 5% and grows revenue 16% in their first year – far in excess of businesses operating without Ramp. We believe every ambitious company deserves the same. If you want to build systems that directly shape how companies move and manage billions, Ramp is the place to do it. About the Role The Data Platform builds infrastructure and tools that enable Ramp to realize business value from data. We partner closely with stakeholder teams to build this infrastructure and the applications on top of it. This role is particularly focused on building platforms that support the data science development lifecycle. You’ll partner with applied scientists, AI engineers, Risk engineers, and other ML developers on building infrastructure and tools that enable and accelerate the development of machine learning models. What You’ll Do Build and integrate the components of Ramp's Analytics Platform and Machine Learning Platform. Build tools that improve the agility and data experience of Ramp's Applied Scientists, AI Engineers, and Risk Engineers. Collaborate with stakeholder teams on building and productionizing machine learning applications. Build reliable, scalable, maintainable, and cost-efficient systems across the stack. What You Need Experience with workflow orchestrators like Airflow, Dagster, or Prefect. Experience building infrast

Strata Information Group (SIG) is a trusted leader in higher ‑ education technology consulting, supporting colleges and universities with ERP/SIS modernization, digital transformation, CRM, cybersecurity, and strategic advisory services. As a long ‑ standing and deeply embedded partner within the higher ‑ education sector, SIG brings together technical depth, operational insight, and a culture rooted in integrity, collaboration, and exceptional client service. Our heritage is built on hands ‑ on expertise, genuine relationships, and a commitment to delivering value with humility and excellence—values that continue to define us as we scale. Full Stack Engineer – Higher Ed Platforms Node.js / React · Client-facing designation: Technical Consultant Location: Pune, India (Hybrid) Reports To: Lead – India Center of Excellence Employment Type: Full-time (engaged through SIG’s Employer of Record in India) Experience: 3–5 years Working Hours: Flexible, with 3–4 hours of daily overlap with US Eastern morning About SIG Strata Information Group (SIG) is a US-based leader in higher-education technology consulting. We help colleges and universities modernize the systems that run their institutions — student information, HR, and finance — through ERP/SIS implementation, integration, digital transformation, CRM, and cybersecurity work. We are building our first engineering Center of Excellence in Pune. This is a founding-team role. You will not be joining a large delivery pool with a fixed process — you will help set how this team builds. The Role This is a software engineering job. You will spend most of your time writing and shipping code. You will take functional specifications and turn them into working software across three areas: application integrations, Experience Card development for user-facing functionality, and workflow automation using Ellucian’s workf

We believe that the way people interact with their finances will drastically improve in the next few years. We’re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid’s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Seattle, Washington D.C., Raleigh, London, and Amsterdam. About the Team The Embedded Insights team supports Plaid’s mission to build a world-class suite of intelligence products. We identify the best opportunities to use machine learning in Plaid products, prove out those opportunities, and collaborate with cross-functional partners to turn them into real-world production systems. About the Role As a Senior Machine Learning Engineer on Embedded Insights, you will help shape Plaid’s future by building machine learning-powered products and features. You will initially support the Plaid App, working on a 0-to-1 consumer-facing product and helping establish product-market fit for a new business line. You will work closely with product managers, data scientists, engineers, customers, and other machine learning engineers to translate ambiguous opportunities into effective ML systems that create measurable customer value. In supporting the Plaid App, you will: Build machine learning-based features for a 0-to-1 consumer-facing product. Partner with product managers to translate ambiguous business requirements into machine learning problems and influence product strategy and roadmap decisions. Rapidly iterate and experiment to help drive product

About the Team OpenAI’s API Multicloud team is responsible for extending OpenAI’s API platform into strategic cloud environments, starting with AWS . The team’s mission is to distribute OpenAI’s API broadly and safely by enabling key API technologies in cloud-native environments, in close partnership with Amazon and internal teams across Codex, Research, Safety Systems, and Applied. The team is focused on bringing core developer and enterprise capabilities into cloud-native environments, including cloud-hosted Codex, model customization / post-training as a service, and new stateful runtime environments for agentic workloads. This work sits at the intersection of production ML systems, developer platforms, model behavior, and large-scale infrastructure. About the Role We’re looking for a backend engineer who can quickly understand OpenAI’s models, products, and systems, then adapt first-party deployments for other cloud platforms. You’ll build backend services, APIs, SDK integrations, authentication flows, and cloud service infrastructure that let developers use OpenAI capabilities in the cloud environments where they already build. This role involves working across teams, sometimes embedded with partner product groups, to ship products quickly and across multiple platforms at the same time. It’s a strong fit for engineers who have built developer tools, especially AI-powered tools, communicate clearly across technical boundaries, and can shape architectures that support different deployment models; experience building cloud services is a strong plus. In this role, you will: Build backend and infrastructure systems that extend OpenAI’s API platform into cloud-native environments, like AWS. Design and ship cloud-contained products that allow customers to use OpenAI capabilities while keeping workloads and data within cloud environments. Help stand up cloud-hosted Codex experiences powered by the OpenAI Responses API. Build the infrastructure and runtime abstractions

Overview We are seeking a hands-on Director of AI Software Engineering to lead and scale AI engineering efforts supporting multiple business units across Governance, Risk, and Compliance (GRC). This role sits at the intersection of product delivery, platform evolution, and applied AI—driving real-world impact across core workflows. This is not a pure management role. We are looking for a builder who leads from the front, someone who has recently written production code, shipped systems end-to-end, and can operate comfortably in ambiguity while aligning teams and stakeholders. What You’ll Do Lead AI Engineering Across GRC Own delivery of AI-powered capabilities embedded directly into business unit workflows (e.g., risk analysis, compliance automation, reporting, due diligence) Partner with product, data, and platform teams to translate business problems into scalable AI systems Stay Hands-On Contribute to architecture, code reviews, and critical path implementation Prototype and validate new approaches (LLMs, agents, retrieval systems, classification pipelines, etc.) Set engineering standards for performance, reliability, and cost efficiency Build and Scale Teams Lead and mentor a high-performing team of AI/ML and software engineers Drive hiring, coaching, and career development Establish a culture of ownership, speed, and technical excellence Drive Execution Deliver production-grade systems—not experiments Balance speed with rigor (security, privacy, compliance) Operate across multiple concurrent initiatives with clear prioritization Communicate and Influence Act as a bridge between engineering and business stakeholders Clearly articulate trade-offs, risks, and outcomes to senior leadership Align cross-functional teams around shared goals and timelines What We’re Looking For Proven Builder 10+ years in software engineering, with recent hands-on coding experience Demonstrated track record of shipping production systems at scale Experience with modern

NVIDIA has been redefining computer graphics, PC gaming, and accelerated computing for more than 25 years. Today, we are tapping into the unlimited potential of AI to define the next era of computing. As an NVIDIAN, you will address challenges spanning architecture, silicon, firmware, software, and production — and excellent judgment matters as much as technical depth! Every major NVIDIA silicon product family—from the chips powering AI and datacentre systems to gaming, professional, embedded, and automotive platforms—passes through our productization work on its way to production. NVIDIA’s Silicon Co-Design Productization team works from pre-silicon strategy and feature development through bring-up, characterization, correlation, and optimization. Our charter spans power & performance modelling, bring up & tuning of low-power features, power & thermal controllers , and system-level optimization that ultimately shape how NVIDIA products are configured, binned, specified, and shipped. What you'll be doing Drive silicon power productization from pre-silicon planning through bring-up and production, including test strategy, feature readiness, characterization, and optimization. Partner with architecture and design teams to identify improvements, validate features, and help translate them into production-ready solutions. Correlate measured silicon behaviour with pre-silicon expectations, investigate gaps, and drive complex issues to root cause. Build power and performance models and characterization methodologies that decide silicon binning, product specifications, productization decisions, and customer guidance. Use AI/ML and data-driven methods to analyse characterization & telemetry data, identify anomalies & trends , and accelerate issue debug across silicon, board, power delivery, firmware,