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Member Of Applied Ai Architect Mumbai in Toronto

98 active opportunities · Updated October 2026

Explore current member of applied ai architect mumbai jobs in Toronto. Filter by work mode, employment type, experience, department, date posted and distance.

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📍 Toronto, Canada· Full-time
✓ High-confidence listingCompany trend -76.2%
Quick readStrong listing-quality and freshness signals

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. Our ultimate goal is to be a leader in democratizing access to private and public equity markets by making those assets available on-chain and be tradable 24/7. As a Staff Software Engineer in this role, you will work on the most critical projects across Tokenization, Robinhood Chain, and the Robinhood Wallet. Most importantly, you will proactively coach and uplift other team members, drive engineering excellence, and set the highest bar for quality. This role is based in our Toronto office, with in-person attendance expected at least 3 days per week. At Robinhood, we believe in the power of in-person work to accelerate progress, spark innovation, and strengthen community. Our office experience is intentional, energizing, and designed to fully support high-performing teams. What you’ll do Own the technical vision and execution for Robinhood Chain, the Tokenization Engine, and the Robinhood Wallet Design, build, and operate the core services that power Robinhood Chain, the Tokenization Engine, and the Robinhood Wallet Remain deeply hands-on by writing production code, leading complex implementations, and setting the standard for engineering quality across the platform Improve

PythonJavaAWSAI
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📍 Toronto, Canada
✓ High-confidence listingCompany trend -72.4%
Quick readStrong listing-quality and freshness signals

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 autonomous transition is a transformational opportunity for Lyft. Our strategy focuses on becoming the preferred marketplace, fleet, and operational partner for the world's best Autonomous Vehicle (AV) providers. As AV deployments scale across new markets, the operational infrastructure that enables safe, compliant, and high-quality service becomes a critical competitive advantage. This role sits at the heart of that infrastructure - owning the systems, processes, and partner alignment that allow Lyft to operate at the standards our AV partners require and our riders expect. As a qualified candidate, you have a track record of building and running complex operational programs in highly regulated or standards-driven environments. You are energized by cross-functional complexity - comfortable leading structured implementation processes that span many teams while keeping a clear eye on compliance and quality outcomes. You bring a program management mindset, strong stakeholder communication skills, and the judgment to navigate ambiguity in a fast-moving industry. Responsibilities: Own execution of AV partner audits end-to-end. That includes evidence collection, submission, partner and third-party review, mitigation oversight, and closeout, across concurrent certification cycles for multiple markets and AV partners, domestic and international. Act as a strategic leader within the company to support cross-functional teams’ compliance controls and readiness for partner scrutiny Drive coordination across teams including EHS, Legal, Safety, HR, IT and Operations for every deliverable. Translate partner and regulatory requirements into concrete, assignable asks and ensure deadlines are met Maintain and continuously improve the audit tracking system, including the evidence library, audit trail, and submissi

Artificial IntelligenceLogisticsHR
L
📍 Toronto, Canada
✓ High-confidence listingCompany trend -72.4%

From C$40/hr

Quick readStrong listing-quality and freshness signals

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. Content Systems is the heart of Lyft's language ecosystem. The team is made up of two distinct disciplines, Content Design and Learning Experience Design, who create and own language across Lyft's in-app experiences that help customers succeed on the Lyft platform. We're looking for a Content Systems intern to join our team for the summer. This role will both help design and build our internal content system (think information architecture), and embed in a rotation of design teams as a content design/learning design partner in building products across the Lyft community. Of course, you won’t be alone. You'll work with designers, researchers, marketers, and product managers day in and day out to develop experiences that reach and resonate with riders. This internship will take place in our Toronto office during Summer 2027 . What we're looking for Responsibilities: Support our content system by establishing and translating information architecture to help manage content across Lyft Help teams reconsider existing systems and processes (eg publishing workflows) to align to the new information architecture Support product strategy and vision through content, working on projects as a content designer and learning experience designer Translate complicated concepts into clear in-product copy (UI, notifications, errors, and more) and learning materials Collaborate with designers, visual content creators, researchers, engineers, marketers, data science, product managers, and other stakeholders across tech and ops The ability to translate concepts across the UI, learning center, and knowledge base into connected content objects Manage multiple projects and competing priorities Maintain, evolve and champion the Lyft brand voice and style Skills: Excellent writing skills; ability to

Artificial IntelligenceAI
L
📍 Toronto, Canada
✓ High-confidence listingCompany trend -72.4%
Quick readStrong listing-quality and freshness signals

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. Lyft is looking for software engineers from a scope of disciplines. We are growing our team with people who want to build, improve and incorporate technologies that make the lives of our community more enriched. As an engineer at Lyft, you'll collaborate with teams like product, data science, analytics, and operations on code that empower us to iterate quickly, while focusing on delighting our passengers and drivers. The Rider organization is focused on building a seamless, best-in-class rideshare experience for riders. From the foundational functionality of requesting a ride to the tailored interactions with your flight, we sweat the small stuff to help make Lyft the best transportation solution. As an Senior Software Engineer on the Rider Team, you will work hand in hand with various teams across Lyft, fostering collaboration, and driving innovation to improve riders' experience with rideshare. Responsibilities: Write well-crafted, well-tested, readable, maintainable code Participate in code reviews to ensure code quality and distribute knowledge Participate in our teams oncall rotation. Identify, triage, debug and resolve issues/bugs across our various applications and platforms Have the ability to explain the various trade offs made in decisions Manage project priorities, deadlines, and deliverables. Partner with product managers, designers, and other engineering teams to build complex features and products from idea to positive execution Analyze our internal systems and processes and locate areas for improvement/automation Share your knowledge by giving brown bags, tech talks, and promoting appropriate tech and engineering best practices Provide technical mentorship and feedback to junior engineers Help establish roadmap and architecture based on technology and our needs Experience: B

AWSAzureGCPDocker
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📍 Toronto, Canada
✓ High-confidence listingCompany trend -72.4%
Quick readStrong listing-quality and freshness signals

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 Driver team is dedicated to fostering a platform of high-quality service by empowering drivers to perform their best. We are looking for a product-minded engineer who wants to build and improve products that sit at the center of the core driver experience. Products you drive will solve pain points that matter most to drivers by streamlining key interactions, reducing friction, and creating systems that feel intuitive, fair, and supportive. As an engineer at Lyft, you'll collaborate with teams like product, data science, analytics, and operations on code that empower us to iterate quickly, while focusing on delighting our passengers and drivers. Responsibilities: Design and implement backend features end-to-end with clear ownership, delivering well-scoped work from technical design through to production with moderate guidance from senior engineers Write clean, reliable, well-tested code that meets team standards and holds up in code review Participate actively in code reviews, giving specific and constructive feedback while continuing to develop your own review instincts Debug and resolve issues across backend services including performance bottlenecks, reliability problems, and data integrity issues Collaborate with product managers, designers, and partner engineering teams to clarify requirements and surface technical constraints early Contribute to technical discussions and help evaluate implementation approaches for new features Write unit and integration tests for your own code and develop familiarity with the team's broader testing and observability practices Address technical debt and make incremental improvements to existing services as part of regular development work Participate in on-call rotations, respond to production incidents, and support teammates in mitigating custome

PythonJavaAWSGCP
L
📍 Toronto, Canada
✓ High-confidence listingCompany trend -72.4%
Quick readStrong listing-quality and freshness signals

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. Lyft is building the next generation of intelligent agents powered by AI. We're seeking a Senior AI Agentic Engineer to lead this transformation across the enterprise. This is a strategic role for someone who can bridge the gap between AI technology and business value, designing and deploying AI-powered workflows that deliver measurable outcomes. You'll work across IT, people operations, marketing, sales, finance, legal, and procurement to architect AI-first solutions that solve complex business problems. Responsibilities: Architect and implement AI agents and intelligent workflows that transforms complex, multi-step business processes and deliver quantifiable business outcomes Partner with business leaders and stakeholders across multiple departments to identify high-impact AI opportunities that align with organizational objectives Elicit requirements from diverse stakeholders and translate complex business problems into technical solutions Build compelling business cases that clearly articulate ROI, implementation costs, benefits, timelines, and strategic alignment Evaluate, recommend, and implement AI solutions that best fit organizational needs and use cases Design solutions with an AI-first approach, ensuring optimal value delivery and user experience Monitor and measure the performance of AI workflows, using data-driven insights to demonstrate value and drive continuous improvement Design and deliver training programs, workshops, office hours, and enablement materials that help teams understand and adopt agentic solution Create frameworks, best practices, templates, and reusable patterns that accelerate AI adoption and ensure consistent quality Build a community of practice around AI and intelligent agents, empowering others to identify opportunities and contribute to the agentic roadmap Act as

AWSGCPArtificial IntelligenceAI
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📍 Toronto, Canada· Full-time
✓ High-confidence listingCompany trend -72.4%

From C$46/hr

Quick readStrong listing-quality and freshness signals

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. With over half a billion rides and counting, Lyft is solving hard problems in a flourishing domain with a lot of data and creative solutions in Marketplace, Mapping, Fraud, Growth and beyond. We're actively building the next-generation Machine Learning (ML) platform for low-cost, ultra-immersive transportation to improve people’s lives using modern ML with peta-byte scale data. Our Machine Learning Engineers are excited to work on these challenging problems and redefine solutions to directly impact various aspects of Lyft's primary business. If you are a student with experience in machine learning workflows, passionate about solving challenging problems using data and working in a dynamic, creative, and collaborative environment, this opportunity is for you! Responsibilities: Contribute to the design, build, train and test of Machine Learning models Write production-level code to convert ML models into working pipelines Partner with Product Managers, Data Scientists, and fellow ML Engineers to frame Machine Learning problems within the business context Analyze experimental and observational data, communicate findings to support decisions Participate in code and spec reviews to ensure code quality and distribute knowledge Experience: Currently pursuing a Bachelor's, Master's, or PhD degree in Computer Science or a related technical field from a university in Canada (required) , with a graduation date between December 2027 and Summer 2028 (required). For any candidates who are master's students who worked between their bachelor's and master's programs: candidates should also have less than 2 years of relevant full-time work experience Available during Summer 2027 for the internship in Toronto Good understanding and knowledge of ML libraries like scikit-learn, Tensorflow, PyTorch, Keras, MXNet, et

PythonMachine LearningAIGo
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📍 Toronto, Canada· Full-time
✓ High-confidence listingCompany trend -72.4%

From C$102K/yr

Quick readStrong listing-quality and freshness signals

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. Data is at the heart of Lyft’s products and decision-making. You will leverage data and rigorous, analytical thinking to shape our products and make business decisions. This will involve performing rigorous product deep dives, identifying opportunities for product enhancements, and measuring the impact of product changes. The Airports team, within the Driver organization, focuses on the airport marketplace and the unique products designed for this use case. Airports are one of the most important, impactful, and complex parts of Lyft’s Rideshare business, as they are a key part of both the rider and driver Lyft experience and have unique dynamics. As an Analytics Lead on the Airport team, you will collaborate with our team of engineers, product managers, and designers to conduct thorough data deep dives on airport performance, challenge our current strategy, and recommend enhancements to facilitate market growth. The ideal candidate can apply strong business acumen to propose product and marketplace changes, and is comfortable working with a highly cross functional team. In this role, you will help us tackle problems such as: How should we determine pricing and earnings for airport rides? Who are our current airport drivers and what segment can we focus on to grow our supply? How does this strategy interact with driver bonuses? Which airports are underperforming and which key metrics can we use to identify and classify airport performance? What targets should we set for these key metrics and how do we efficiently monitor these metrics? What is driving high cancellation rates today and which types of riders/drivers are cancelling? What product changes can we implement to reduce cancellation rates? How are riders and drivers using different ride modes at airports, and how do we design

L
📍 Toronto, Canada· Full-time
✓ High-confidence listingCompany trend -72.4%

From C$108K/yr

Quick readStrong listing-quality and freshness signals

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. Data Science is at the heart of Lyft’s products and decision-making. You will leverage data and rigorous, analytical thinking to shape our products and make business decisions. This will involve identifying and scoping opportunities, shaping team priorities, recommending and implementing technical solutions, designing experiments, and measuring the impact of new features. The Airports team, within the Driver organization, focuses on the airport marketplace and the unique products designed for this use case. Airports are one of the most important, impactful, and complex parts of Lyft’s Rideshare business, as they are a key part of both the rider and driver Lyft experience and have unique dynamics. As a Data Scientist on the Airport team, you will collaborate with our team of engineers, product managers, and designers to think critically about the current rider and driver experience and implement product enhancements to facilitate market growth. The ideal candidate can apply strong business acumen to propose product changes, develop end-to-end technical solutions, and is comfortable working with a highly cross functional team. In this role, you will help us tackle problems such as: What rider segments are present at airports and how can we address their major pain points to grow our airport marketshare? What new airport product features can we introduce to grow rider demand? Are we able to forecast rider demand and use this prediction to adjust ride offerings or improve the rider experience? How can we optimize ride offerings for each rider to maximize conversion? Responsibilities Define and implement decision frameworks, measurement strategies, and scientific methodologies that bring consistency and rigor to business decisions and forecasts, balancing opportunity and uncertainty Desi

PythonSQLAIGo
L
📍 Toronto, Canada
✓ Quality checkedCompany trend -72.4%

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. Data Science is at the heart of Lyft’s products and decision-making. Data Scientists at Lyft operate in dynamic environments, moving quickly to build the world’s best transportation solutions. We tackle a wide range of challenges - from shaping long-term business strategy with data, to making critical short-term decisions, to developing algorithms and models that power both internal systems and customer-facing products. Driver Incentives Science owns the algorithms and systems behind incentive design, influencing driver engagement and marketplace efficiency — from real-time supply positioning to longer-horizon earnings and engagement programs. The team is responsible for designing pay and incentive mechanisms that are efficient and good for driver experience over the long run. As a Data Scientist specializing in Algorithms, you'll partner closely with product, engineering, and operations leaders to build and scale incentive systems, shape long-term mechanism design strategy, and deliver on critical business goals tied to marketplace efficiency and driver earnings. Candidates with strong optimization backgrounds — think mathematical programming, control theory, or operations research — are a great fit, though we welcome strong candidates from machine learning or causal inference as well. The ideal candidate thrives in a fast-paced environment and brings a hands-on, entrepreneurial mindset to drive results. Responsibilities: Collaborate with engineering and product teams to design, implement, and iterate on new features and algorithmic improvements for driver incentives and pay mechanisms. Design, develop, and deploy optimization models, algorithms, and systems for problems such as budget allocation, multidimensional cost-curve development, and incentive targeting. Write production model code; collabor

PythonMachine LearningArtificial Intelligence
L
📍 Toronto, Canada· Full-time
✓ High-confidence listingCompany trend -72.4%

From C$108K/yr

Quick readStrong listing-quality and freshness signals

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. Marketplace teams are at the heart of our products and decision-making, owning everything from rider pricing to driver earnings, incentives, and efficient matching. We’re looking for passionate, driven engineers to build systems that empower our riders and drivers to have the best transportation experience possible through prediction, adaptivity, and personalization. We’re looking for someone who is excited about working in a fast-paced, innovative, and impactful environment to create reliable solutions to distributed computing, ML, and data problems. The Pricing team is a centerpiece of Lyft’s Marketplace org, determining prices for all rideshare products and supporting new initiatives. Rider Engagement develops rider-facing engagement levers and optimizes user pricing experience to drive both short term and long term business outcomes. We work with Product & Science to solve and implement complex pricing requirements, balancing the needs of riders, drivers, and the business goals. As an owner of one of the most critical flows in the company, you will work on a wide array of challenges such as latency-sensitive concurrency problems, large scale distributed systems, and experimentation. If you’re interested in playing a large part in demand / supply management and improving the Lyft customer experience, this could be a great fit for you. Responsibilities: Drive high-impact projects and innovate new solutions to provide the best user experience. Work closely with cross-functional teams and partner teams to develop solutions based on technology and business needs, and advance team’s goals and priorities Independently lead features from idea to positive execution and launch Unblock, support and communicate with internal partners to achieve results Write well-crafted, well-tested, readable, maintaina

PythonAWSRestAI
L
📍 Toronto, Canada· Full-time
✓ High-confidence listingCompany trend -72.4%

From C$108K/yr

Quick readStrong listing-quality and freshness signals

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. Data Science is at the heart of Lyft’s products and decision-making. Data Scientists at Lyft operate in dynamic environments, moving quickly to build the world’s best transportation solutions. We tackle a wide range of challenges - from shaping long-term business strategy with data, to making critical short-term decisions, to developing algorithms and models that power both internal systems and customer-facing products. Driver Incentives Science owns the algorithms and systems behind incentive design, influencing driver engagement and marketplace efficiency — from real-time supply positioning to longer-horizon earnings and engagement programs. The team is responsible for designing pay and incentive mechanisms that are efficient and good for driver experience over the long run. As a Data Scientist specializing in Algorithms, you'll partner closely with product, engineering, and operations leaders to build and scale incentive systems, shape long-term mechanism design strategy, and deliver on critical business goals tied to marketplace efficiency and driver earnings. Candidates with strong optimization backgrounds — think mathematical programming, control theory, or operations research — are a great fit, though we welcome strong candidates from machine learning or causal inference as well. The ideal candidate thrives in a fast-paced environment and brings a hands-on, entrepreneurial mindset to drive results. Responsibilities: Collaborate with engineering and product teams to design, implement, and iterate on new features and algorithmic improvements for driver incentives and pay mechanisms. Design, develop, and deploy optimization models, algorithms, and systems for problems such as budget allocation, multidimensional cost-curve development, and incentive targeting. Write production model code; collabor

PythonMachine LearningAIGo
L
📍 Toronto, Canada· Full-time
✓ High-confidence listingCompany trend -72.4%

From C$108K/yr

Quick readStrong listing-quality and freshness signals

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. To fulfill Lyft’s mission of creating the real-time transportation network of the future, Lyft needs engineers from a scope of disciplines. We need engineers to help us intelligently scale our backend infrastructure, to increase pricing in real time given localized supply and demand data, to predict future localized demand, to create delightful and intuitive UX flows for passengers and drivers, to improve our cloud infrastructure orchestration and monitoring, to increase dispatched driver-passenger pairings based on real-time data and real-world edge cases, to build tools to increase the efficiency of our customer service team, and more. You're an enthusiastic and experienced app developer looking to take your skills to the next level by joining our iOS team. You’re excited about scaling millions of lines of Swift code and hundreds of mobile developers. Our app is used by millions of people, and we take great pride in our work. This means excellent development practices, careful code architecture, and an organization built around rapid releases. Our codebase is written entirely in Swift with modern design patterns and coding standards. We rely on 3rd party libraries and contribute back to the community (including the Swift language itself). Responsibilities Help establish roadmap and architecture based on technology and our needs Write well-crafted, well-tested, readable, maintainable code Participate in code reviews to ensure code quality and distribute knowledge Share your knowledge by giving brown bags, tech talks, and promoting appropriate tech and engineering best practices Performing thoughtful code reviews for colleagues, and help others by conducting high-quality code reviews Participate in hiring activities: take part in technical interviews, live coding, share detailed feedback to hir

ReactAISwiftExcel
O
📍 Toronto, Ontario, Canada· Full-time
✓ High-confidence listingCompany trend -63.6%

From C$136K/yr

Quick readStrong listing-quality and freshness signals

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. Auth0 is growing rapidly and looking for exceptional new team members to help take us to the next level. One team, one score. We never compromise on identity. You should never compromise yours either. We want you to bring your whole self to Auth0. If you're passionate, practice radical transparency to build trust and respect, and thrive when you're collaborating, experimenting and learning – this may be your ideal work environment. We are looking for team members that want to help us build upon what we have accomplished so far and make it better every day. N+1 > N. About the Team Here at Auth0 we’re focused on securing the world’s identities so innovators can innovate. We’re currently hiring a senior Full Stack Software Engineer to join our Acquisitions and Activation Team . This team owns the crucial first impressions of the Auth0 ecosystem. We apply rigorous, data-driven experimentation and A/B testing to optimize the entire early customer journey—from the moment a developer signs up, to the precise second they hit their "ah-ha" moment. We bridge the gap between deep technical infrastructure and user psychology, building primarily on a JavaScript ecosystem (Node.js and React) . If you are a full-stack engineer who loves blending robust software architecture with rapid, metrics-driven experimentation, this is the team for you. What You Will Do Optimize the Acquisition Funnel: Own, build, and continuously scale the entire signup experience to reduce fric

JavaScriptJavaReactNode.js
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📍 Toronto, Canada· Full-time
✓ High-confidence listingCompany trend -72.4%

From C$1.4M/yr

Quick readStrong listing-quality and freshness signals

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 Safety and Customer Care (SCC) team at Lyft manages over 1.7 million monthly human and AI interactions and serves as Lyft's primary direct touchpoint with riders and drivers. We handle critical infrastructure that powers both human associates and AI agents to make riders and drivers feel safe and comfortable while riding or driving with Lyft, transforming every support interaction into a moment of genuine connection. Agentic AI is at the center of how we scale that mission. We fine-tune and align open-source models, build AI-powered support agents, and develop end-to-end AI agents for safety case management, systems that reason over complex, high-stakes cases and drive them to resolution. SCC brings together ML, data, backend, and product engineers alongside data scientists and operations partners to transform these systems. As a Machine Learning Engineer on the SCC team, you will fine-tune and align models and build AI Agents that power how riders and drivers get help. Your work spans the full loop: post-training open-source models for our domain, composing them into multi-step agents, and building the evaluation that proves they are safe to ship in a customer-facing, safety-critical setting. Post-train and adapt open-source LLMs for SCC use cases using SFT, LoRA, and preference-tuning methods (RLHF, RLAIF, RLVR). Design and build AI-powered support agents and end-to-end agents for safety case management using LangGraph or equivalent agentic frameworks. Own the evaluation data flywheel, offline and online, that defines what "good" looks like and build benchmarks for the team to hill-climb. Turn interaction feedback into training data and learning signals, closing the data flywheel that continuously improves the models. Responsibilities: Conduct literature review and build post-training fra

PythonMachine LearningAIGo
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