Machine Learning Engineer Radar Jobs

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 Reporting to the Director of Quality & Performance, this role as Engineering Manager of Performance & Resilience will drive performance and resiliency improvements for the Auth0 product at Okta. Here you'll be working with some of the most advanced technology in the space, helping to streamline and secure billions of access requests a year. In this role, you will work closely with architects, platform team members, and product engineers to build the testing infrastructure that keeps Auth0 performant at scale — including the frameworks, tooling, and realistic datasets that make that testing meaningful. The ideal candidate is passionate about software quality and architecture, a self-starter, intellectually curious, and brings deep experience with performance testing, load testing frameworks, dataset generation, performance analysis, monitoring tooling, and chaos engineering. What you’ll be doing Collaborate with architects, tech lead, product owners, security and operations engineers to implement best practices related to performance and resiliency Communicate and organize cross-team projects with high business

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 Opportunity The Migration Services team builds the critical, data-driven services that seamlessly move customers across environments in real-time. We are looking for an Engineering Manager to lead, mentor, and grow this pivotal team.This is a unique opportunity to shape the team's technical direction and culture from the ground up, and you will be helping build and hire for this team. You are a people-focused leader who is also deeply technical, capable of guiding architectural decisions and willing to be hands-on when needed. This role requires extensive collaboration with numerous Product teams and a close partnership with our Customer Service organization, which utilizes the tooling your team builds to execute customer migrations. If you are passionate about building high-performing teams, driving technical strategy, and delivering high-impact projects, we want to hear from you. What You'll Achieve Build and lead a world-class team. You will recruit, mentor, and support a team of skilled engineers, fostering a strong, collaborative culture and keeping the team motivated and engaged. Own the roadmap and execution. You will partner with product and stakeholder teams to define the team's strategy and roadmap. You'll be responsible for prioritizing work and ensuring the team consistently delivers high-quality, reliable services. Drive engineering excellence. You will hold the team to a high standard of quality, reliability, and operational robustn

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 Mapping team at Lyft is tasked with building a digital representation of the physical world - a map. We collect and serve the freshest and most accurate mapping data possible, along with algorithms, models, platform services, and map-based user experiences that power Lyft’s current and future transportation offerings. Mapping represents a huge opportunity for Lyft’s business, but also a big challenge. We build and scale systems that deal with large data storage, real-time data processing, machine / deep learning pipelines, routing and ETA models, driver and passenger location tracking, and more. We built beautiful and magical user experiences on top of all those services, and compete with companies that have been in the mapping business for decades. Our engineering team is growing rapidly, and we are looking for Engineering Managers to help us scale. Our engineers are smart, flexible, and love solving difficult challenges. They look to their managers for organizational transparency, career development, mentorship, and honest feedback. They move fast and ship code to production continuously, relying on their leadership to increase productivity by removing obstacles and keeping processes lean. Responsibilities: Manage a rapidly growing team of engineers developing user-facing Mapping experiences Mentor and guide the professional and technical development of your team members. Help develop their careers and assign them to projects tailored to their skill levels, personalities, work styles, and professional goals Build teams that are collaborative, inclusive, and respectful of each other Provide continuous feedback, address underperformance, and recognize the individual strengths and contributions of your team members Create plans for prioritizing technical and resourcing challenges in your organizat

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 Mapping team at Lyft is tasked with building a digital representation of the physical world - a map. We collect and serve the freshest and most accurate mapping data possible, along with algorithms, models, platform services, and map-based user experiences that power Lyft’s current and future transportation offerings. Mapping represents a huge opportunity for Lyft’s business, but also a big challenge. We build and scale systems that deal with large data storage, real-time data processing, machine / deep learning pipelines, routing and ETA models, driver and passenger location tracking, and more. We built beautiful and magical user experiences on top of all those services, and compete with companies that have been in the mapping business for decades. Our engineering team is growing rapidly, and we are looking for Engineering Managers to help us scale. Our engineers are smart, flexible, and love solving difficult challenges. They look to their managers for organizational transparency, career development, mentorship, and honest feedback. They move fast and ship code to production continuously, relying on their leadership to increase productivity by removing obstacles and keeping processes lean. Responsibilities : Manage a rapidly growing team of engineers developing user-facing Mapping experiences Mentor and guide the professional and technical development of your team members. Help develop their careers and assign them to projects tailored to their skill levels, personalities, work styles, and professional goals Build teams that are collaborative, inclusive, and respectful of each other Provide continuous feedback, address underperformance, and recognize the individual strengths and contributions of your team members Create plans for prioritizing technical and resourcing challenges in y

We are now looking for an AI Developer Technology Engineer Interns. Intelligent machines powered by AI computers that can learn, reason and interact with people are no longer science fiction. Today, a self-driving car can meander through a country road at night and find its way. An AI-powered robot can learn motor skills through trial and error. This is truly an extraordinary time — the era of AI has begun. Image recognition and speech recognition — GPU Deep Learning has provided the foundation for machines to learn, perceive, reason and solve problems. The GPU started out as the engine for simulating human creativity, conjuring up the amazing virtual worlds of video games and Hollywood films. Now, NVIDIA's GPU runs Deep Learning algorithms, simulating human intelligence, and acts as the brain of computers, robots and self-driving cars that can perceive and understand the world. Just as human creativity and intelligence are linked, computer graphics and artificial intelligence come together in our architecture. Two modes of the human brain, two modes of the GPU. This may explain why NVIDIA GPUs are used broadly for Deep Learning, and NVIDIA is increasingly known as “the AI computing company.” Come join a team full of world-class computer scientists to work in its Compute Developer Technology team as an AI Developer Technology Engineer. What you will be doing: Work and develop state of the art techniques in LLM/AIGX/GR, and perform in-depth analysis and optimization to ensure the best possible performance on current- and next-generation GPU architectures You will provide the best AI solutions using GPUs working directly with key customers Collaborate closely with the architecture, research, libraries, tools, and system software teams to influence the design of next-generation architectures, software platforms, and

Position: Mechanical Engineer Location: Austin, Texas Job Overview: Infinitum is looking for a full-time Mechanical Engineer to work on site in our fan engineering team. In this role you will be a key contributor in developing proprietary commercial and industrial fan systems for Infinitum. Key Responsibilities: Conduct product design and development following general design guidelines and tools including CAD programs. Conduct calculations and analysis using closed-form methods, computer applications, and FEA and other simulation tools. Develop calculation tools for specific problems. Support other departments and customers by addressing technical questions under general design guidelines. Review drawings, schematics, bills of material, and other documentation necessary to manufacture, test, install, and commission products. Create and enhance specific design guidelines by leveraging past experience and technical learning. Develop new products by providing input on specifications, designing and building prototypes, devising validation tests, and preparing supporting documentation. Provide input to project feasibility and cost analysis. Participate in product improvement, productivity improvement, standardization, cost reduction, and cycle time reduction initiatives. Lead some of these initiatives. Provide disposition to non-conformances and participate in corrective actions providing technical input based on established design guidelines. Qualifications and Skills Must-Have Skills: Bachelor's degree (B.S.) from a four-year college or university in Engineering or Physical Science with 4+ years of related work experience, or an equivalent combination of education and experience. Basic design knowledge of machined components, sheet metal parts, castings, and injection molded components. Proficiency in SolidWorks (CSWP preferred), including sheet metal design and generating manufacturing drawings. Understanding of ASME Y14.5 GD&T and how to apply

About Hark Hark is an artificial intelligence company building advanced, personalized intelligence. One that is proactive, multimodal, and capable of interacting with the world through speech, text, vision, and persistent memory. We're pairing that intelligence with next-generation hardware to create a universal interface between humans and machines. While today's AI largely operates through chat boxes and decade-old devices, Hark is focused on what comes next: agentic systems that interact naturally with people and the real world. To get there, we're developing multimodal models and next-generation AI hardware together - designed from the ground up as a single, unified interface for a new era of intelligent systems. About the Role At Hark, you'll lead the development for the foundation of agentic reinforcement learning (RL) environments: the digital worlds in which AI agents learn to use software, navigate complex workflows, and act on their surroundings. Our ambition is to simulate the breadth and complexity of the internet, connecting websites, apps, services, and artifacts into rich, stateful environments, with the potential to evolve dynamically over time. This is a chance to shape both the worlds agents learn in and the systems that make learning at scale possible. You'll build environments end-to-end and work closely with researchers to bring them into RL training and evaluation. You'll also develop the infrastructure behind our agent gym, making these environments easy to integrate, reproduce, and scale across heterogeneous execution targets. Responsibilities Build agent environments and simulations end-to-end, including frontend interfaces, backend services, APIs, data models, tools, and realistic workflows used to train and evaluate AI agents. Build the infrastructure that powers our agent gym, including orchestration, sandboxing, packaging, benchmarking, and systems for running environments across heterogeneous targets. Create interconnected simulations w

About Ema Ema builds AI Employees for HR, IT and Finance. Our AI Employees take on the busy work across the employee experience, from recruiting, onboarding and benefits to IT support, invoice processing and payroll, so people can spend their time on work that needs them. Founded by former executives from Google, Coinbase, Flipkart, and Okta, our team includes engineers from premier tech companies and graduates of Stanford, MIT, UC Berkeley, CMU, and IITs. We are backed by industry leading investors including Accel, Naspers/Prosus, Creaegis, Section32, and angels like Sheryl Sandberg and Dustin Moskovitz. Headquartered in Silicon Valley and with offices in London, Bangalore and Vancouver, Ema is at the frontier of what Agentic AI can do in production. We ship real systems that run real business processes at scale. The Role We are looking for an Engineering Leader to manage and scale multiple product lines in the Voice, BPO, and Workforce Management space. This is a high-impact leadership role that sits at the intersection of real-time voice systems, operations research, and data-intensive platform engineering. You will report directly to the Head of Engineering and own the engineering organization that builds the infrastructure powering Ema’s Voice AI Employees, Agent QA, auto-learning pipelines, rich analytics, and workforce optimization capabilities — all operating as scalable, multi-tenant systems deployed across global geographies. You will collaborate with Product, ML/AI, and Go-to-Market teams to translate customer needs into production systems that handle high volumes of voice data, deliver real-time insights, and continuously improve through automated learning loops. As the owner of multiple product lines, you will balance roadmap priorities across Voice, BPO operations, and WFM (work force management) — ensuring each product evolves cohesively while meeting distinct customer needs. What You Will Do Scalable Multi-Tenant Systems Architect and build multi-ten

About Ema Ema builds AI Employees for HR, IT and Finance. Our AI Employees take on the busy work across the employee experience, from recruiting, onboarding and benefits to IT support, invoice processing and payroll, so people can spend their time on work that needs them. Founded by former executives from Google, Coinbase, Flipkart, and Okta, our team includes engineers from premier tech companies and graduates of Stanford, MIT, UC Berkeley, CMU, and IITs. We are backed by industry leading investors including Accel, Naspers/Prosus, Creaegis, Section32, and angels like Sheryl Sandberg and Dustin Moskovitz. Headquartered in Silicon Valley and with offices in London, Bangalore and Vancouver, Ema is at the frontier of what Agentic AI can do in production. We ship real systems that run real business processes at scale. The Role We are looking for an Engineering Leader to manage and scale multiple product lines in the Voice, BPO, and Workforce Management space. This is a high-impact leadership role that sits at the intersection of real-time voice systems, operations research, and data-intensive platform engineering. You will report directly to the Head of Engineering and own the engineering organization that builds the infrastructure powering Ema’s Voice AI Employees, Agent QA, auto-learning pipelines, rich analytics, and workforce optimization capabilities — all operating as scalable, multi-tenant systems deployed across global geographies. You will collaborate with Product, ML/AI, and Go-to-Market teams to translate customer needs into production systems that handle high volumes of voice data, deliver real-time insights, and continuously improve through automated learning loops. As the owner of multiple product lines, you will balance roadmap priorities across Voice, BPO operations, and WFM (work force management) — ensuring each product evolves cohesively while meeting distinct customer needs. What You Will Do Scalable Multi-Tenant Systems Architect and build multi-ten

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Anthropic is looking for a Senior Partner Account Manager (PAM) to own our relationship with one to two of the world's largest global systems integrators. This is a general-management role disguised as an alliance role: you will set the multi-year joint strategy with the partner's C-suite, negotiate the strategic agreement that underpins it, and then build the machine — go-to-market, solution co-development, delivery readiness, and enablement at a scale of tens of thousands of practitioners — that turns Claude into one of the partner's largest and fastest-growing practices. You will be measured on the size and health of the joint business: progress against a $1B+ Claude practice plan, Anthropic ARR sourced and influenced through the partner, certified and delivery-ready practitioners (50,000+), co-developed solutions in market with reference-able customers, and the depth of executive alignment on both sides. Key responsibilities Own the joint business. Build and run a multi-year joint business plan with each GSI covering services bookings, Anthropic ARR, priority industries and geographies, investment, and headcount. Report on it to Anthropic and partner executive leadership quarterly. Lead at the C-suite. Be the primary Anthropic relationship owner for the partner's Group CEO, service-line and industry CEOs, CTO/Chief AI Officer, and Chief Learning Officer. Map and activate Anthropic executive sponsors, run CEO-level QBRs, and shape the partner's public AI narrative (earnings calls, analyst days, flagship events) around Claude. Negotiate the strategic agreement. Structure and close multi-year strategic collaboration ag

Incident Manager US Remote CSQ127R151 At Databricks, we are passionate about empowering data teams to tackle the world’s most challenging problems — from bringing the next mode of transportation to reality to accelerating the development of medical breakthroughs. We achieve this by building and operating the world’s best data and AI infrastructure platform, enabling our customers to leverage deep data insights and enhance 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 an Incident Manager, you will lead Databricks’ most critical production incidents while providing clear, accurate, and timely communication to customers, executives, and engineers. You’ll serve as both incident commander and reliability engineer; orchestrating multi-team responses, driving real-time status updates, and partnering with engineering to analyze and prevent failures. Your work will ensure Databricks maintains not only technical resilience but also customer and stakeholder confidence during high-impact events. This role combines operational leadership, technical systems knowledge, and exceptional communication skills. You will be at the intersection of engineering depth and operational clarity, ensuring that every major incident is managed with precision, transparency, and continuous improvement. The impact you will have here: Lead critical incidents — coordinate multi-disciplinary response efforts across Databricks’ cloud-based services to rapidly mitigate impact and restore operations. Drive technical root cause analysis and reliability improvements: collaborate with engineering teams to trace and document underlying causes across distributed systems, services, and data stores. Summarize key learnings, clearly communicate action items, and ensure

Job Requisition ID # 26WD101494 Machine Learning Operations Developer, Inference, AI/ML Platform L'affichage de poste en français suivra / The French job posting follows Position Overview Autodesk, a global leader in 3D design, engineering, manufacturing, and entertainment software, is seeking an MLOps Developer to join our AI/ML Platform team. This role will contribute to ensuring the smooth operationalization of machine learning models and the overall efficiency of our next-generation AI/ML platform used in the development of machine learning and generative AI solutions powering Autodesk’s suite of products and services. You will collaborate with research and product engineering teams from various domains including design, construction, manufacturing, and media & entertainment to support platform operations. The role is hybrid Toronto or Montreal. Responsibilities Contribute to the operational excellence of our AI/ML Platform by implementing and optimizing MLOps practices Develop and maintain automated deployment pipelines for machine learning models, supporting seamless transitions from development to production Collaborate with cross-functional teams to design, implement, and maintain scalable infrastructure for model training, inference, and data processing <li style="color:#1d

About Pinterest: Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product. Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the flexibility to do your best work. Creating a career you love? It’s Possible. At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI. Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here . Pinterest is a visual discovery platform where hundreds of millions of people come to find inspiration and decide what to try, buy, or do next. Our Ads Quality organization builds the machine-learning systems that make ads relevant and valuable to Pinners while delivering meaningful outcomes for advertisers. We are seeking a Director of Machine Learning Engineering to lead a broad portfolio of Ads Quality modeling teams focused on engagement, conversion, ROAS optimization, ranking, representation learning, and ML-powered experimentation. In this role, you will shape and drive a unified technical strategy across Ads Quality, leading teams responsible for engagement ranking, oCPM and conversion modeling, ROAS optimization, lightweight ranking and retrieval models, foundation model adoption, sequence and multimodal modeling, and the quality and eff

About Pinterest: Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product. Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the flexibility to do your best work. Creating a career you love? It’s Possible. At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI. Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here . We’re looking for a strategic and experienced engineering leader to define the technical direction for Pinterest’s advertiser measurement and signal-quality ecosystem. In this role, you’ll lead managers and senior technical leaders across Interfaces, Ingestion, User Match, and Conversion Quality, driving multi-year investments in machine learning, data platforms, experimentation, privacy, and production reliability. You’ll partner closely with Product, Data Science, Ads Quality, Infrastructure, Privacy, Legal and Sales to translate complex advertiser and business challenges into scalable solutions—and build an inclusive, high-performing organization equipped to deliver measurable impact at scale. What you’ll do: Define technical strategy and investment priorities across Interfaces, Ingestion, User Match, and Conversion Quality. Lead

Bracebridge Capital, LLC is a leading alternative asset manager with approximately $12 billion of net assets under management. The firm pursues investment strategies primarily within the global fixed income markets with the objectives of capital preservation and absolute return without significant correlation to equity, interest rate and foreign exchange markets. Established in 1994, Bracebridge manages private investment funds that serve endowments, foundations, pension funds and other institutional and high-net-worth investors. Approximately 170 employees operate from our office located in Boston’s historic Back Bay. The entrepreneurial and collaborative culture at Bracebridge rewards and supports motivated, dedicated, enthusiastic and intellectually curious individuals. We believe our firm’s greatest asset is the people who work here. We are seeking a Machine Learning Analyst to join the growing data analytics and machine learning team. The team’s primary mission is to develop machine learning systems to answer open-ended investment questions and support portfolio management decisions. The team works across the project lifecycle and technical stack, from ideation, understanding and analyzing data, hypothesis generation and testing, and model development all the way through to the deployment and maintenance of models and systems in production. Our work spans statistical modeling, classical machine learning, and modern AI and LLM techniques. The Machine Learning Analyst’s primary responsibility will be to contribute to these efforts alongside other team members. Over time, you will develop the technical and domain expertise needed to take increasing ownership of individual components and ultimately end-to-end projects. The work is highly collaborative and spans quantitative research, software engineering, and machine learning. Analysts work with other members of the machine learning team and portfolio managers to translate loosely defined investment ide