Technical Partner Manager Salary India in Canada

We're transforming the grocery industry At Instacart, we invite the world to share love through food because we believe everyone should have access to the food they love and more time to enjoy it together. Where others see a simple need for grocery delivery, we see exciting complexity and endless opportunity to serve the varied needs of our community. We work to deliver an essential service that customers rely on to get their groceries and household goods, while also offering safe and flexible earnings opportunities to Instacart Personal Shoppers. Instacart has become a lifeline for millions of people, and we’re building the team to help push our shopping cart forward. If you’re ready to do the best work of your life, come join our table. Instacart is a Flex First team There’s no one-size fits all approach to how we do our best work. Our employees have the flexibility to choose where they do their best work—whether it’s from home, an office, or your favorite coffee shop—while staying connected and building community through regular in-person events. Learn more about our flexible approach to where we work. Why this role is on the menu We are looking for a seasoned Oracle Fusion ERP Technical Analyst to join our Financial Systems team and accelerate a portfolio of Order-to-Cash (O2C), Record-to-Report (R2R) and Procure to Pay (P2P) transformation initiatives. In this role you will own the design, development, and delivery of custom reports, data integration interfaces, document templates, and REST/SOAP API solutions within Oracle Fusion Cloud — enabling finance and cross-functional stakeholders to operate with greater speed and accuracy. The Financial Systems team owns the technology backbone for Instacart's finance operations, managing Oracle Fusion, Zip, Billing Platform, OIC, HighRadius, Workiva, and FloQast. We partner closely with Finance, Platform Engineering, and the CTO organization to drive transformation initiatives that scale with the business. You'l

Most security assurance work is reactive: a customer asks, a team scrambles, an answer goes out. This role exists to end that cycle. As a Senior Staff Analyst, you’ll own a named portfolio of our most significant customers from a security perspective, and get ahead of what they need — their regulatory environment, their audit calendar, their risk appetite, their control expectations — well enough to have the evidence ready before the request arrives. You’ll lead customer security audits hands-on, sit across from customer security teams as a peer rather than a form-filler, and build account security plans that make the next assessment predictable instead of painful. This is deliberately a hands-on senior individual contributor role. You’ll spend your time in audits, in customer conversations, and in the detail of controls and evidence — not in a management chain. If you’ve got deep SOC 2 and ISO 27001 knowledge, real technical range across cloud architecture, identity and vulnerability management, and the presence to hold a room with a sceptical CISO, this is a portfolio you can genuinely own. Here’s a breakdown of what you’ll do (not all of it, just the important stuff): Own a portfolio of strategic accounts as their dedicated security point of contact, building durable relationships with their security, risk, compliance and procurement teams. Lead customer security audits and assessments hands-on — scoping, preparing evidence, running the sessions, defending control design and driving findings to closure with internal owners. Build and maintain an account security plan for each account: their frameworks and regulators, audit and reassessment cycles, known concerns, open items and the roadmap commitments they care about. Anticipate requirements before they’re raised, tracking regulatory change, industry expectations and each account’s compliance calendar so documentation and evidence are staged in advance. Act

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. We are hiring a Marketing Technology Lead to own Lyft's B2B marketing technology stack, spanning marketing automation, content and web, lead routing, data enrichment, and attribution. As the senior technical owner of that stack, you will lead solution design, own the architecture and data model that carry a lead from first touch through to a qualified opportunity, and partner with Marketing Operations, Sales Operations, Sales Technology, Privacy, Legal, and Data to translate business needs into durable, scalable systems. This is a hands-on leadership role for someone who knows B2B marketing operations, can build the systems that run them, and is looking for ways to bring AI into how the stack works, not just what it produces. Responsibilities: Serve as the senior technical owner of the B2B marketing technology stack, from solution design through delivery, adoption, and ongoing support. Lead requirements gathering with Marketing Operations, Sales Operations, Sales Technology, and Data partners, and translate them into functional and technical designs. Remain hands-on, configuring and extending the marketing automation platform (HubSpot) across workflows, forms, lead scoring, and custom objects, and building the integrations that connect the stack. Own the marketing technology roadmap and architecture, including the lead and account data model, enrichment and routing logic, and integrations with the CRM, data platform, web, and advertising systems. Own the tracking and instrumentation layer, including tag management, site and campaign tracking, and the data capture behind attribution. Own the lead lifecycle systems, partnering with Sales Operations and Sales Technology on lead identity, deduplication, scoring, routing, MQL and SQL definitions, and funnel stage integrity. Identify where AI can im

We're transforming the grocery industry At Instacart, we invite the world to share love through food because we believe everyone should have access to the food they love and more time to enjoy it together. Where others see a simple need for grocery delivery, we see exciting complexity and endless opportunity to serve the varied needs of our community. We work to deliver an essential service that customers rely on to get their groceries and household goods, while also offering safe and flexible earnings opportunities to Instacart Personal Shoppers. Instacart has become a lifeline for millions of people, and we’re building the team to help push our shopping cart forward. If you’re ready to do the best work of your life, come join our table. Instacart is a Flex First team There’s no one-size fits all approach to how we do our best work. Our employees have the flexibility to choose where they do their best work—whether it’s from home, an office, or your favorite coffee shop—while staying connected and building community through regular in-person events. Learn more about our flexible approach to where we work. Overview The Ads DSE team builds the core capabilities that power Instacart's off-platform advertising, secure data collaboration (cleanrooms), automated taxonomy management, and their associated platform foundations. We are hiring a Senior Engineer II (L6) to co-own the technical roadmap, modernize our data solutions infrastructure, scale off-platform integrations and measurement capabilities, extend our cleanroom collaboration capabilities, and automate taxonomy change management workflows. This role is pivotal for cross-team collaboration, developer productivity, and AI-driven development initiatives. You are a senior technical leader who designs and ships scalable, data‑intensive systems; drives cross‑team execution; and raises engineering standards. You’ll partner closely with Product, Data Science, Data Platform, and Governance teams to build reusable abstrac

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 Staff Software Engineer Opportunity Passkeys, powered by FIDO2 WebAuthn, are revolutionizing how people authenticate—bringing us into a passwordless future that’s more secure and seamless than ever before.At Okta, we’re on a mission to help enterprises and consumers embrace this transformation. We’re building cutting-edge phishing-resistant authenticators and passkey solutions that make security stronger while making life easier for users. Our products empower businesses to leave passwords behind and defend against modern threats with innovative, user-friendly technology. We are looking for a Staff Software Engineer to join the Passwordless team. As a Staff Engineer, you will be a technical leader, making large, independent contributions and shaping the future of how millions of users access technology securely. This is a role for an engineer who thrives on solving ambiguous problems and taking ownership of end-to-end solutions. You will not only execute on complex technical challenges but also influence the team's direction, mentor other engineers, and proactively identify opportunities to improve our products and processes. If you are passionate about building highly reliable, scalable systems and want to define the future of passwordless authentication, we’d love for you to join us. What you’ll be doing Partner closely with product, design, and other cross-functional stakeholders to own problem spaces and ensure we are building the right solutions fo

Join us in building the future of finance. Our mission is to democratize finance for all. An estimated $124 trillion of assets will be inherited by younger generations in the next two decades. The largest transfer of wealth in human history. If you’re ready to be at the epicenter of this historic cultural and financial shift, keep reading. ABOUT THE TEAM + ROLE We are building an elite team, applying frontier technologies to the world's biggest financial problems. We're looking for bold thinkers. Sharp problem-solvers. Builders who are wired to make an impact. Robinhood isn't a place for complacency, it's where ambitious people do the best work of their careers. We're a high-performing, fast-moving team with ethics at the center of everything we do. Expectations are high, and so are the rewards. The AI R&D team is at the core of Robinhood's product intelligence. Our mission is to build and scale high-impact models that power personalization, search, social feeds, fraud detection, and risk management for millions of Robinhood users. We operate as a cross-functional partner to growth, product, and data engineering—translating complex financial data into intelligent systems that make Robinhood smarter for every customer. We move fast, raise the bar, and care deeply about building things that matter. If you've ever wanted to solve personalization problems no one else has cracked—in one of the most data-rich, regulated industries on the planet—this is the team for you! As a Staff Machine Learning Engineer on the AI R&D team, you will own the design and delivery of sophisticated personalization and recommendation systems that directly shape what millions of users see and do on the Robinhood platform. You'll be a technical anchor on a growing, high-caliber team — collaborating with product, data engineering, and fellow ML engineers to take ambitious ideas from zero to one and into production at scale. You'll help define the team's technical direction, mentor engine

The Team + The Role Pendo’s Professional Services team is part of the broader Strategy & Transformation organization. The team helps customers transform how they operate, not just how they use Pendo, through technical and strategic consulting. This work spans complex technical engagements, including system migrations, integrations, and data work, as well as advisory support that helps customers evolve their processes, teams, and ways of working. As a Sr. Professional Services Engineer Consultant, you will own the design and delivery of complex technical engagements. You will work at the intersection of product, data, and engineering, extending Pendo’s capabilities through custom integrations, data pipelines, APIs, and technical solutions that connect Pendo to customers’ broader ecosystems. You will partner with consultants and Customer Engineers to deliver outcome-driven engagements that accelerate time to value and enable long-term customer success. This role is based in Raleigh, San Francisco or remote What this looks like day-to-day Engagement design and scoping: Partner with Account Directors and Customer Engineers to qualify Professional Services opportunities and distinguish transformation gaps from tooling gaps. Lead scoping conversations with customer stakeholders, define the problem, validate appetite, design engagement structures, and author Statements of Work that are commercially sound and delivery-ready. Custom integrations and data solutions: Design and build technical solutions that extend Pendo’s capabilities and integrate with customer systems. Write production-quality code, build APIs, design data pipelines, and implement ETL processes across data warehouses, analytics platforms, BI tools, and emerging AI/ML systems. Technical project delivery: Own multiple complex technical projects end-to-end, including data engineering and system integration work. Lead execution, troubleshoot issues, provide technical leadership on escalated engagements, and

Scale Labs, Research Scientist — Agent Robustness As the leading data and evaluation partner for frontier AI companies, Scale plays an integral role in understanding the capabilities and safeguarding AI models and systems. Building on this expertise, Scale Labs has launched a new team focused on policy research, to bridge the gap between AI research and global policymakers to make informed, scientific decisions about AI risks and capabilities. Our research tackles the hardest problems in agent robustness, AI control protocols, and AI risk evaluations to help governments, industry, and the public understand and mitigate AI risk while maximizing AI adoption. This team collaborates broadly across industry, the public sector, and academia and regularly publishes our findings. We are actively seeking talented researchers to join us in shaping this vision. As a Research Scientist working on Agent Robustness you will work on the fundamental challenges of building AI agents that are safe and aligned with humans. For example, you might: Research the science of AI agent capabilities with a focus on how they relate to safety, risk factors, and methodologies for benchmarking them; Design and build harnesses to test AI agents’ tendency to take harmful actions when pressured to do so by users or tricked into doing so by elements of their environment; Design and build exploits and mitigations for new and unique failure modes that arise as AI agents gain affordances like coding, web browsing, and computer use; Characterize and design mitigations for potential failure modes or broader risks of systems involving multiple interacting AI agents. Ideally you’d have: Commitment to our mission of promoting safe, secure, and trustworthy AI deployments in the industry as frontier AI capabilities continue to advance. Practical experience conducting technical research collaboratively. You should be comfortable building and leveraging agent scaffolding, designing evaluation harnesses, an

Scale Labs, Research Scientist — AI Controls and Monitoring As the leading data and evaluation partner for frontier AI companies, Scale plays an integral role in understanding the capabilities and safeguarding AI models and systems. Building on this expertise, Scale Labs has launched a new team focused on policy research, to bridge the gap between AI research and global policymakers to make informed, scientific decisions about AI risks and capabilities. Our research tackles the hardest problems in agent robustness, AI control protocols, and AI risk evaluations to help governments, industry, and the public understand and mitigate AI risk while maximizing AI adoption. This team collaborates broadly across industry, the public sector, and academia and regularly publishes our findings. We are actively seeking talented researchers to join us in shaping this vision. As a Research Scientist focused on AI Controls and Monitoring, you will design methods, systems, and experiments to ensure that advanced AI models and agents remain aligned with intended goals, even in high-stakes or adversarial environments. For example, you might: Develop monitoring techniques and observability methods that track AI behavior in real time to identify and flag deviations, emergent capabilities, or anomalous outputs; Research mechanisms for layered control, including fail-safes, oversight protocols, and intervention methods that can halt or redirect AI systems when risks are detected; Design red-team simulations to probe weaknesses in oversight and control mechanisms, and build mitigations to close identified gaps; Collaborate with policymakers, engineers, and other researchers to establish standards and benchmarks for AI monitoring and escalation. Ideally you’d have: Commitment to our mission of promoting safe, secure, and trustworthy AI deployments in the industry as frontier AI capabilities continue to advance. Practical experience conducting technical research collaboratively. You should be

About Scale AI Scale AI is the data foundation for AI, helping organizations build and deploy reliable production AI applications. We partner with leading enterprises and government organizations to accelerate their AI initiatives through our data annotation platform, generative AI solutions, and enterprise AI capabilities. Role Overview As a Senior Staff Frontier Agents Engineer on our Enterprise team, you'll be the technical bridge between Scale AI's cutting-edge AI capabilities and our most strategic customers. You'll work with enterprise clients to understand their unique challenges, architect custom AI solutions, and ensure successful deployment and adoption of AI systems in production environments. This is a hands-on technical role that combines deep engineering expertise with customer-facing problem solving. You'll work directly with customer engineering teams to integrate AI into their critical workflows. Key Responsibilities Customer Integration & Deployment Partner directly with enterprise customers to understand their technical infrastructure, data pipelines, and business requirements Design and implement custom integrations between Scale AI's platform and customer data environments (cloud platforms, data warehouses, internal APIs) Build robust data connectors and ETL pipelines to ingest, process, and prepare customer data for AI workflows Deploy and configure AI models and agents within customer security and compliance boundaries AI Agent Development Develop production-grade AI agents tailored to customer use cases across domains like customer support, data analysis, content generation, and workflow automation Architect multi-agent systems that orchestrate between different models, tools, and data sources Implement evaluation frameworks to measure agent performance and iterate toward business objectives Design human-in-the-loop workflows and feedback mechanisms for continuous agent improvement Prompt Engineering & Optimization Create sophisticate

Scale Labs, Research Scientist — Frontier Risk Evaluations As the leading data and evaluation partner for frontier AI companies, Scale plays an integral role in understanding the capabilities and safeguarding AI models and systems. Building on this expertise, Scale Labs has launched a new team focused on policy research, to bridge the gap between AI research and global policymakers to make informed, scientific decisions about AI risks and capabilities. Our research tackles the hardest problems in agent robustness, AI control protocols, and AI risk evaluations to help governments, industry, and the public understand and mitigate AI risk while maximizing AI adoption. This team collaborates broadly across industry, the public sector, and academia and regularly publishes our findings. We are actively seeking talented researchers to join us in shaping this vision. As a Research Scientist focused on Frontier Risk Evaluations, you will design and create evaluation measures, harnesses and datasets for measuring the risks posed by frontier AI systems. For example, you might do any or all of the following: Design and build harnesses to test AI models and systems (including agents) for dangerous capabilities such as security vulnerability exploitation, CBRN uplift, and other high-risk activities; Work with government agencies or other labs to collectively scope and design evaluations to measure and mitigate risks posed by advanced AI systems; Publish evaluation methodologies and write technical reports for policymakers. Ideally you’d have: Commitment to our mission of promoting safe, secure, and trustworthy AI deployments in the industry as frontier AI capabilities continue to advance. Practical experience conducting technical research collaboratively. You should be comfortable building and instrumenting ML pipelines, writing evaluation harnesses, and quickly turning new ideas from the research literature into working prototypes. A track record of published research in m

Position Overview As a Solutions Engineer at Diligent, you will partner closely with Sales to help organizations understand how our platform can transform the way they identify and mitigate risk, perform audits, strengthen controls, and operationalize broader GRC programs. You’ll independently lead the SE workstream on small to mid-sized opportunities, while partnering with more senior Solutions Engineers on complex, multi-pillar deals, acting as a trusted partner to customer stakeholders and helping translate Risk & Audit and broader GRC challenges into clear, compelling solutions that drive business value. If you enjoy combining domain expertise, storytelling, solution design, and customer interaction and are looking to build your career in a commercial, customer-facing environment, this is a strong next step. Key Responsibilities Customer & Commercial Partnership Partner with Sales to lead the full pre-sales lifecycle for small to mid-sized opportunities, helping customers understand how Diligent solves real-world risk, audit, and control management challenges. Deliver independent, well-prepared, tailored software demonstrations that clearly articulate business value, while seeking coaching and feedback from senior team members for continuous improvement. Engage confidently with stakeholders across Internal Audit, Risk, Compliance, IT, Controls, and Governance teams, owning day-to-day customer conversations and escalating to senior SEs for high-risk or complex topics as needed. Translate customer pain points into clear solution narratives, including outcomes and success criteria, to support deal progression and closure. Own the technical win for small to mid-sized opportunities, and contribute to the technical strategy on larger, multi-stakeholder deals in partnership with senior SEs. Solution Design & Thought Leadership Design and present solu

About the Role The Machine Learning team at Tubi drives the innovation behind personalized user experiences. With the largest inventory in the industry and hundreds of millions of viewers, we tackle problems in the space of recommendations, search, content understanding, and ads optimization that shape the future of streaming. We are seeking a VP / Director of Machine Learning Engineering to lead and build a high-performing team while staying close to the technical work. This is a hands-on leadership role: you will set the strategic direction for our recommendation, personalization, and ads optimization systems, including recommendation foundation modeling, and you will stay in the algorithms and the code, conducting deep dives into modeling components and guiding the hardest technical decisions yourself. You will tackle complex machine learning problems at scale and partner closely with cross-functional teams to ship solutions that measurably improve how hundreds of millions of viewers experience Tubi. What You’ll Do Lead, build, and grow a high-performing ML engineering team, fostering a culture of technical excellence, ownership, and rapid iteration. Define and drive the ML strategy and long-term technical roadmap for recommendation, personalization, and ads optimization, including recommendation foundation modeling, identifying opportunities for ML to shape Tubi’s broader product and business strategy. Stay hands-on: conduct deep dives into algorithmic components and systems, ensuring models are optimized for both performance and scalability across regions and product areas. Lead the design, development, and implementation of advanced recommendation systems and algorithms, contributing directly to the most challenging technical problems. Build and deploy robust, full-stack ML pipelines: data extraction, feature development, model training, testing, deployment, and serving. Continuously monitor, evaluate, and optimize the performance of deployed models, ensuring

Scale works with the industry’s leading AI labs to provide high quality data and accelerate progress in GenAI research. We are looking for Research Scientists and Research Engineers with expertise in LLM post-training (SFT, RLHF, reward modeling). This role will focus on optimizing data curation and eval to enhance LLM capabilities in both text and multimodal modalities. In this role, you will develop novel methods to improve the alignment and generalization of large-scale generative models. You will collaborate with researchers and engineers to define best practices in data-driven AI development. You will also partner with top foundation model labs to provide both technical and strategic input on the development of the next generation of generative AI models. You will: Research and develop novel post-training techniques, including SFT, RLHF, and reward modeling, to enhance LLM core capabilities in both text and multimodal modalities. Design and experiment new approaches to preference optimization. Analyze model behavior, identify weaknesses, and propose solutions for bias mitigation and model robustness. Publish research findings in top-tier AI conferences. Ideally you’d have: Ph.D. or Master's degree in Computer Science, Machine Learning, AI, or a related field. Deep understanding of deep learning, reinforcement learning, and large-scale model fine-tuning. Experience with post-training techniques such as RLHF, preference modeling, or instruction tuning. Excellent written and verbal communication skills Published research in areas of machine learning at major conferences (NeurIPS, ICML, ICLR, ACL, EMNLP, CVPR, etc.) and/or journals Previous experience in a customer facing role. Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position and may be inclusive of several career levels at Scale; it will be determined du

Scale works with the industry's leading AI labs to provide high quality data and accelerate progress in GenAI research. We are looking for Research Scientists and Research Engineers with expertise in LLM post-training (SFT, RLHF, reward modeling) and evaluation. This role is on the evaluation pod within the GenAI Research Organization and will focus on building benchmarks and diagnosing model failure modes in both text and multimodal modalities. In this role, you will develop rigorous evaluations and diagnostic methods that reveal where frontier models fail and why. You will collaborate with researchers and engineers to define best practices in evaluation-driven AI development. You will also partner with top foundation model labs to translate failure analysis into technical and strategic input on the next generation of generative AI models. You will: Analyze model behavior to identify, characterize, and diagnose failure modes in frontier LLMs and Agents. You’ll identify everything from capability gaps and reasoning errors to robustness and alignment issues, all focusing on RCA. Design and build benchmarks and evaluation methods that measure LLM capabilities in both text and multimodal modalities. Apply post-training expertise (SFT, RLHF, reward modeling) to connect observed failures to the data and training interventions that address them. Publish research findings in top-tier AI conferences. Ideally you’d have: Ph.D. or Master's degree in Computer Science, Machine Learning, AI, or a related field. Deep understanding of deep learning, reinforcement learning, and large-scale model fine-tuning. Experience with post-training techniques such as RLHF, preference modeling, or instruction tuning, and with LLM evaluation or benchmark development. Excellent written and verbal communication skills. Published research in areas of machine learning at major conferences (NeurIPS, ICML, ICLR, ACL, EMNLP, CVPR, etc.) and/or journals. Previous experience in a customer facing r