Engineering Manager, Data Modeling

Who are we? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! Role Overview: As Engineering Manager for our verticals application team, you'll lead a team of engineers building full-stack applications, backend and frontend, that bring AI into critical sectors, starting with the Pharmaceutical industry and expanding into areas like finance and healthcare over time. You'll own the application and user-experience layer, partnering closely with the ML engineering teams who build the underlying data and agent infrastructure. Day to day, that means working with product managers, designers, and ML engineers to ship best-in-class applications, while hiring, mentoring, and growing your team. We're looking for someone who has built AI-first products deeply integrated with agentic systems, and who can deliver secure systems that users can trust in high-stakes environments. Our pace is startup-fast, but the bar is enterprise-high: these applications must be reliable, observable, safe, and auditable from day one. Key Responsibilities: Lead and manage backend and frontend engineers, fostering collaboration and ensuring predictable delivery Act as the primary interface between Product and Engineering tea

Join Truecaller – The place where innovation meets impact! Truecaller's mission is to build trust in communication by making it safer, smarter, and more efficient. Born in Sweden, trusted by the world, and here’s why we stand out: We are trusted by over 500 million active users every month across 190+ countries We identify over 15 billion calls daily, helping users avoid spam and scams We are powered by a team of 400+ employees from 45+ nationalities We always look for people who take initiative, own their work, and keep raising the bar. An entrepreneurial mindset matters here, especially when it turns bold ideas into real actions. We stay collaborative and focused, always searching for smarter paths forward. If you want to make an impact and grow with a team that inspires millions, you’ll fit right in. As an Engineering Manager, you will lead the team behind Truecaller's Recommendations and adVantage, our AI-powered performance advertising platform. It is a multi-disciplinary team of ML engineers, data scientists, backend engineers, and data engineers building the retrieval, ranking, and contextual-bandit systems, and the real-time serving and data infrastructure beneath them, that decides what Truecaller recommends and shows to hundreds of millions of users. The role sits at the intersection of technical depth and people leadership: you will set direction across an applied-ML stack, keep a highly specialized team healthy and growing, and turn a research-heavy roadmap into shipped, reliable systems. What you'll do: Lead, grow, and retain a high-performing team of ML engineers, data scientists, backend engineers, and data engineers, investing deliberately in each person's development and career path. Set technical direction across the recommendation and advertising ML stack - retrieval, ranking, contextual bandits, and conversion modeling - along with the real-time serving and data platforms that support them. Own team planning, prioritization, and delivery, balanci

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. Engineering Manager, Cloud Efficiency Snowflake runs large scale cloud infrastructure to deliver its own service — production and internal deployments, Kubernetes fleets, CI/CD, etc. Our cloud spend is in billions of dollars per year. We are looking for an experienced Engineering Manager to lead the Cloud Efficiency engineering team. In this role, you will own the technical vision and execution for building a unified, self-serve cloud efficiency platform along with AI skills and agents that makes resource usage and spend attributable and governable while driving insights and optimization of our cloud spend. AS AN ENGINEERING MANAGER IN CLOUD EFFICIENCY, YOU WILL: Lead and grow our talented team of software engineers, fostering a culture of technical excellence, ownership, and continuous learning. Drive the roadmap for Cloud Efficiency — translating company-level spend objectives into engineering systems: authoritative cost data, resource ownership registry, attribution pipelines, cost and unit economics modeling, observability, governance policies, and optimization workflows — in partnership with Product, Engineering, Finance, and Data Science. Set technical strategy for backend systems, data pipelines, and APIs that measure, attribute and surface cost and usage insights at

AI only answers correctly when it can trust the data underneath it. This role owns two connected parts of how Sigma shows up in that world: where Sigma's experience lives outside its own product (MCP, a CLI, the Claude and ChatGPT marketplaces, integrations like Slack, Teams, and Glean), and the semantic layer that makes every one of those surfaces trustworthy. The first mandate is Sigma's AI ecosystem: defining Sigma's approach to MCP, giving external agents structured, governed access to Sigma's data model; owning the CLI, giving developers a fast way to work with Sigma outside the UI; and building Sigma's presence in the Claude and ChatGPT marketplaces, plus integrations for Slack, Teams, Glean, and similar surfaces, so people can reach Sigma's data wherever they already work. This is some of the most visible, fastest-growing surface area in the product. The second mandate is the semantic layer underneath it all. Every agent, chat answer, and integration is only as reliable as the data model behind it — get a metric definition wrong here, and every surface built on top inherits the mistake. This includes setting the roadmap for how semantic views connect across data platforms and how the model evolves as new AI capabilities emerge. What you'll do Define Sigma's approach to MCP, giving external agents and tools structured, governed access to Sigma's data model. Own the CLI roadmap, giving developers a fast, scriptable way to work with Sigma outside the UI. Build Sigma's presence in the Claude and ChatGPT marketplaces, along with integrations for Slack, Teams, Glean, and similar surfaces, so people can reach Sigma's data wherever they're already working. Set the roadmap for Sigma's data modeling strategy, including how semantic views connect across data platforms and how the semantic layer evolves as new AI capabilities emerge. Partner with engineering and design to ship integration and semantic modeling capabilities that hold up at enterprise scale.

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 . The Conversion Visibility Modeling team enables a performant ads marketplace and helps prove value to advertisers by connecting Pinterest onsite activity with conversions that happen offsite (both digital and physical) in a privacy-preserving way. As a Machine Learning Engineering Manager on this team, you will lead a hybrid team of ML engineers and backend software engineers to build end-to-end identity and conversion visibility solutions across modeling, serving, and data infrastructure, so advertisers retain accurate, privacy-aware performance visibility as signals fragment and degrade. You will set the technical direction for high-impact ML systems that feed ranking, bidding, measurement, and reporting across Pinterest’s ads stack. What you’ll do: Attract, hire, develop, and lead a hybrid team of ML engineers and backend softwar

Sigmoid empowers enterprises to make smarter, data-driven decisions by blending advanced data engineering with AI consulting. We collaborate with some of the world’s leading data-rich organizations across sectors such as CPG-retail, BFSI, life sciences, manufacturing, and more to solve complex business challenges. Our global team specializes in cloud data modernization, predictive analytics, generative AI, and DataOps, supported by 10+ delivery centers and innovation hubs, including a major global presence in Bengaluru and operations across the USA, Canada, UK, Netherlands, Poland, Singapore, and India. Recognized as a leader in the data and analytics space, Sigmoid is backed by Peak XV Partners and has consistently received accolades for innovation and rapid growth. Highlights include being named a ‘Leader’ in ISG’s Specialty Analytics Services for Supply Chain (2024), a two-time ‘India Future Unicorn’ by Hurun India, and a four-time honoree on both the Inc. 500 and Deloitte Technology Fast 500 lists. Technical Lead – Data Engineering As a Technical Lead, you will be responsible in building a highly-scalable and extensible big data platform that provides the foundation for collecting, storing, modeling, and analyzing massive data sets from multiple channels. This position reports to Engineering Manager. Responsibilities: Align Sigmoid with key Client initiatives Interface daily with customers across leading Fortune 500 companies to understand strategic requirements Connect with VP and Director level clients on a regular basis. Travel to client locations Ability to understand business requirements and tie them to technology solutions Facilitate in Technical Aspects Design, develop and evolve highly scalable and fault-tolerant distributed components using Big data technologies. Excellent experience in Application development and support, integration development and data management. Provide technical leadership and manage it day to day basis Guiding developers