Jobs in Canada

Staff Mobile Engineer in Canada

191 active opportunities · Updated October 2026

Explore current staff mobile engineer jobs across Canada. Filter by work mode, employment type, experience, department, date posted and distance.

SA
📍 San Francisco, Canada· Full-time
✓ High-confidence listing

From $302.4K/yr

Quick readStrong listing-quality and freshness signals

About Scale At Scale AI, our mission is to accelerate the development of AI applications. For 8 years, Scale has been the leading AI data foundry, helping fuel the most exciting advancements in AI, including: generative AI, defense applications, and autonomous vehicles. With our recent Series F round, we’re accelerating the abundance of frontier data to pave the road to Artificial General Intelligence (AGI), and building upon our prior model evaluation work with enterprise customers and governments, to deepen our capabilities and offerings for both public and private evaluations. About the ACE team The Agent Capabilities & Environments (ACE) team, part of Scale’s Research organization, brings together customer-facing Researchers and Applied AI Engineers. Our core mission includes research on agent environments and RL reward signals, benchmarking autonomous agent performance across real-world scenarios and environments, creating robust data programs to improve Large Language Models (LLMs) agentic capabilities and building foundational tools and frameworks for evaluating models as agents. ACE focuses on autonomous agents that dynamically interact with diverse external environments, including code repositories, GUI interfaces, browsers, and more. About This Role This role is at the intersection of cutting-edge AI research and practical application, with a focus on studying the data types essential for building state-of-the-art agents, such as browser and SWE agents. The ideal candidate will explore the data landscape needed to advance intelligent, adaptable AI agents, guiding the data strategy at Scale to drive innovation. This position requires not only expertise in LLM agents and planning algorithms but also creativity in addressing novel challenges related to data, interaction, and evaluation. You will contribute to impactful research publications on agents, collaborate with customer researchers, and work alongside the engineering team to translate t

SQLAWSGCPRest
SA
📍 San Francisco, Canada· Full-time
✓ High-confidence listing

From $264.8K/yr

Quick readStrong listing-quality and freshness signals

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. About the General Agents Team The General Agents team, part of Scale’s Enterprise organization, builds robust general agents for customer use cases and applications. The team sits at the intersection of frontier agent development and real-world deployment, translating state-of-the-art reasoning and agentic capabilities into reliable, production-grade systems that drive real economic value. Our agents are scalable systems built around recurring enterprise problem domains, with a strong emphasis on generalization, extensibility, and deployment across many customers. About the Role As a Senior/Staff Machine Learning Engineer (MLE) on the General Agents team, you’ll play a critical role in designing, building, and deploying production-ready AI agents that solve high-impact enterprise problems. You will work across the full agent lifecycle—from model and system design to evaluation, deployment, and iteration—bridging cutting-edge agentic techniques with the constraints and requirements of real customer environments. You will: Design and implement end-to-end agent systems that combine LLM reasoning, tool use, memory, and control logic to solve recurring enterprise use cases. Build scalable, reliable agent architectures that can be deployed across many customers with varying data, tools, and constraints. Develop evaluation frameworks, datasets, environments, and metrics to measure agent performance, reliability, and business impact in production settings. Collaborate closely with product managers, customers, data annotators, and other engineering teams to translate enterprise requirements into robust agent designs. Productionize frontier agent techniques (e.g.,

PythonAWSRestMachine Learning
T
📍 Toronto, Ontario, Canada· Full-time
✓ High-confidence listing
Quick readStrong listing-quality and freshness signals

Tenstorrent is leading the industry on cutting-edge AI technology, revolutionizing performance expectations, ease of use, and cost efficiency. With AI redefining the computing paradigm, solutions must evolve to unify innovations in software models, compilers, platforms, networking, and semiconductors. Our diverse team of technologists have developed a high performance RISC-V CPU from scratch, and share a passion for AI and a deep desire to build the best AI platform possible. We value collaboration, curiosity, and a commitment to solving hard problems. We are growing our team and looking for contributors of all seniorities. We are looking for a Staff Digital Design Engineer to help define, build, and optimize high-performance IP and SoC architectures for next-gen AI and compute workloads. This role is ideal for engineers who thrive at the intersection of microarchitecture, RTL implementation, and performance-aware design. This role is hybrid, based out of Toronto, Ottawa, Boston, or Austin. We welcome candidates at various experience levels for this role. During the interview process, candidates will be assessed for the appropriate level, and offers will align with that level, which may differ from the one in this posting. Who You Are A digital design expert with a deep understanding of computer architecture and IP microarchitecture. Skilled in RTL development (Verilog/VHDL) and familiar with full ASIC flows. Comfortable optimizing for power, performance, and area (PPA) under aggressive design goals. A naturally collaborative and technical engineer — you thrive in spec definition, peer reviews, and team-wide planning. What We Need Architecture and RTL implementation of Tenstorrent’s custom IP blocks and SoC components. Performance-aware design decisions for compute, interconnect, or memory-heavy blocks. Occasional contributions to validation using emulation, FPGA prototyping, or UVM flows. Strong synthesis and timing closure awareness to support backend

AWSGitAIGo
DU
📍 San Francisco, Canada· Full-time
✓ High-confidence listing
Quick readStrong listing-quality and freshness signals

About the Team The Consumer Engineering Team is responsible for helping consumers discover and order everything they love globally. Our work spans the entire consumer journey across homepage, search, store discovery, item exploration, checkout and post checkout. We aim to craft a hyper-personalized, delightful and frictionless experience for millions of our customers. About the Role As a Senior Staff Machine Learning Engineer on Core Cx, you will set the personalization (P13n) strategy for the entire consumer shopping journey and bring that strategy to life. You will use our robust data and machine learning infrastructure to implement new ML solutions to make the consumer search experience more relevant, seamless, and delightful across restaurant, grocery, retail and all business at DoorDash . You will modernize the recommendation system leveraging AI. You will demonstrate a strong command of production level machine learning, experience with solving end-user problems, and collaborate well with multi-disciplinary teams. You're excited about this opportunity because you will… Drive the engineering vision, strategy, and execution for an organization of 150+ Grow, build, and nurture impactful business-focused product engineering teams. Scale the team by developing leaders internally and attracting world-class talent Mentor and guide a fast-growing organization in setting the right architectural patterns, working with various vendors in the space, and making judicious investments in the right areas anticipating what the company needs a few years down the road. Partner with Business, Product, and other Engineering teams to transform DoorDash from local commerce to agentic commerce We're excited about you because you have… B.S. or M.S. in Computer Science or equivalent. 10+ years of industry experience developing machine learning models with business impact, and shipping ML solutions to production. Proficiency in using AI coding tools (e.g., Claude Code) in th

AWSGitRestMachine Learning
R
📍 Toronto, Canada
✓ Quality checkedCompany trend -76.2%

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 Core Infrastructure team's mission is to build and evolve the foundational platform that every Robinhood engineering team builds on — owning the systems, primitives, and developer-facing abstractions that power 24/7 trading, crypto, and global expansion. We treat infrastructure as a product: reliable, fast to provision, and invisible to the teams above it. As a Senior Staff Software Developer on Core Infrastructure, you will own the architectural evolution of three deeply interconnected domains: service mesh and connectivity, compute platform, and infrastructure provisioning. Your decisions will directly shape engineering velocity, operational reliability, and Robinhood's ability to expand to new regions and markets. This is not an operations role — it's a once-in-a-platform-lifecycle opportunity to redesign the foundation before complexity becomes permanent! This role is based in our Toronto, ON 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-p

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

From C$216K/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. Lyft connects people to transportation to change the way we live and get around our communities. We are looking for a Senior Staff Technical Program Manager who brings exceptional technical and analytical skills to drive execution across high-impact product initiatives. Come be part of a team at Lyft focused on enabling and empowering engineering teams to deliver at scale. Technical Program Managers at Lyft drive cross-functional initiatives, leveraging strong leadership, planning, communication, and collaboration skills. Our TPMs are technically strong with deep product and software engineering experience. They are problem solvers who make things happen by setting clear goals and inspiring teams to deliver. TPMs at Lyft are both strategic and tactical, doing what it takes to successfully deliver top-priority programs that have a material impact on the business. This role will support product-facing teams within Rideshare, focusing initially on the Partnerships, Loyalty and Payments organization, where you will be responsible for helping them to create a singular loyalty offering that is accessible, emotional, rewarding, and which makes it simple to choose Lyft. You will collaborate with engineering, product, data science, design, analytics, and operations to drive iterative delivery that delights our riders and drivers. Responsibilities Lead cross-functional product initiatives from ideation through planning, execution, launch, and post-launch — ensuring alignment, accountability, and measurable outcomes at every phase. Provide hands-on support across all phases of the software development lifecycle, including project planning, resource allocation, progress tracking, risk mitigation, KPI ownership and measurement, and leadership communications. Partner with engineering, product, data science, design

SA
📍 San Francisco, Canada· Hybrid
✓ High-confidence listing
Quick readStrong listing-quality and freshness signals

About Snorkel At Snorkel, we believe meaningful AI doesn’t start with the model, it starts with the data. We’re on a mission to help enterprises transform expert knowledge into specialized AI at scale. The AI landscape has gone through incredible changes since 2015, when Snorkel started as a research project in the Stanford AI Lab, to the generative AI breakthroughs of today. But one thing has remained constant: the data you use to build AI is the key to achieving differentiation, high performance, and production-ready systems. We work with some of the world’s largest organizations to empower scientists, engineers, financial experts, product creators, journalists, and more to build custom AI with their data faster than ever before. Excited to help us redefine how AI is built? Apply to be the newest Snorkeler! In September 2026 we raised a $350 million Series E at a $3.5 billion valuation , and we are scaling our engineering and research teams to meet demand. The role Frontier AI data is expensive to make and hard to measure. Every task we deliver is tested against the strongest models, often through many long-running agent rollouts. Your job is to make that process faster, cheaper, and more rigorous with ML and AI You will be one of the early members of ML & Research Engineering at Snorkel. You will study how frontier-grade data is generated and evaluated, form hypotheses, validate them against real production data, and ship the winners at scale. You will shape the discipline's direction, its standards, and the team that grows around it. What you'll work on Efficient agentic evals. Cut the cost of long-horizon agent evaluation with adaptive sampling, statistically grounded early stopping, model cascades, caching, and cheap-first gating. AI model routing. Route every eval and judge call to the cheapest model that clears the quality bar, with fallback, monitoring, and cost attribution. Fine-tuned small models. Fine-tune and serve open-weight models (LoRA and other

PythonMachine LearningAI
T-
📍 Toronto, Canada· Full-time
✓ High-confidence listing
Quick readStrong listing-quality and freshness signals

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 highly skilled Staff Machine Learning Engineer to contribute to transformative projects in video personalization. In this role, you will design and implement advanced algorithms and systems to improve our personalization strategy. As a senior technical expert, you will tackle complex problems in machine learning at scale, collaborating closely with cross-functional teams to develop and optimize machine learning-driven solutions. This is a hybrid role in our Toronto office. What You'll Do: Lead the design, development, and implementation of advanced recommendation systems and algorithms for a global audience Conduct deep dives into algorithmic components and systems, ensuring that models are optimized for both performance and scalability across multiple regions and product areas Build and deploy high-impact robust ML pipelines, including data extraction, feature development, model training, testing, and deployment Continuously monitor, evaluate, and optimize the performance of deployed models, ensuring they meet business goals and provide high-quality user experiences. Work closely with Product, Engineering, and Data Science teams to align on product requirements, set expectations, and deliver machine learning-driven solutions that improve user engagement Your Background: 8+ years of industry experience building production Machine Learning systems MSc or Ph.D. in Computer Science, Machine Learning, Statistics, Mathematics, or a related field Experience with deep learning technologies for recommendation systems, including TensorFlow, PyTorch, or similar frameworks Proficiency in building and deploying full-stack machine le

Machine LearningAIGoSEM
C
📍 Canada· Full-time
✓ Quality checkedCompany trend -91.5%

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! Why this role? Design and implement novel research ideas, ship state of the art models to production, and maintain deep connections to academia and the government. We have one of the highest ratio of compute to engineers in the world. We do not delineate strongly between engineering and research. Everyone will contribute to writing production code and conducting research depending on individual interest and organizational needs. We have all the compute, data, and talent available for you to do your best work. As a Member of Technical Staff - Sovereign AI, you will: Design, build and scale agentic AI systems for serving mission critical use cases. Research, implement, and experiment with ideas on our supercompute and data infrastructure. Learn from and work with the best researchers in the field. Execute across the full AI stack and ship products to serve public interest. You may be a good fit if you have: Canadian citizenship and eligibility for security clearance ( required for this role ). Extremely strong software engineering skills. Proficiency in Python and related ML frameworks. Experience training, evaluating, and using (

PythonGitRestAI
C
📍 Toronto, Ontario, Canada· Full-time
✓ Quality checkedCompany trend -91.5%

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! Why this role? As a Senior Machine Learning Engineer specializing in synthetic data, you will play a pivotal role in developing the synthetic data pipeline that is crucial to Cohere’s advanced language models. Your responsibilities will encompass the end-to-end management of synthetic data, including maintaining and optimizing the synthetic data pipeline, data analysis and generation, as well as conducting data ablations and model evaluation to gauge data quality. You will work with diverse web data and code data and transform them using generative models to improve token efficiency and model quality. By combining research and engineering, you will bridge the gap between raw data and cutting-edge AI models, directly contributing to improvements in critical training metrics like throughput and accelerator utilization. Your work will be essential to Cohere’s mission of delivering efficient and reliable language understanding and generation capabilities, driving innovation in natural language processing. If you are passionate about transforming data into the foundation of AI systems, this role offers a unique opportunity to make a

PythonGitRestMachine Learning
C
📍 Toronto, Ontario, Canada· Full-time
✓ Quality checkedCompany trend -91.5%

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! About the role We're hiring a Marketing Chief of Staff to keep Cohere's marketing org moving at full speed without coming apart at the seams. You'll report to the VP of Brand and work across the whole function: brand, editorial, design, product marketing, demand generation, and integrated marketing. This is not a strategy-only role, and it isn't a glorified project-management seat either. In any given quarter the org is shipping product launches, field events, partner campaigns, and demand programs in parallel, often across regions and time zones. That pace is the reason the role exists. Your job is to make sure the right work wins when everything feels urgent, that plans turn into shipped work, and that the VP of Brand and the leadership team spend their time leading instead of firefighting. Be clear-eyed about the shape of the work. A lot of it is operational: the planning calendar, the budget, the headcount plan, the weekly business reviews, the cross-functional handoffs that break when nobody owns them. The grind is the job. You should want that part, not tolerate it. One boundary worth naming up front. Marketing Ops owns th

GitRestAIGo
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