We're looking for a Staff Data Scientist to help define Asana's growth strategy as users increasingly discover and adopt software through LLM interfaces like ChatGPT, Claude, and Gemini. With millions of knowledge workers now starting their workday in conversational AI tools, we're at an inflection point in how productivity software reaches users. You'll drive Asana's acquisition playbook for the emerging LLM-driven channels and re-imagine new customer onboarding in the AI-era. As part of the PLG organization, you'll leverage data to influence how new users discover, learn about,  and decide to start using and paying for Asana.

Asana's Data Science team helps us fulfill our mission by informing strategy, defining success metrics, and identifying new ways to deliver user value. Data scientists are at the crux of deepening our understanding of the customers and driving more business outcomes by leveraging experimentation, causal inference, statistical and machine learning techniques, and data storytelling.

This role is based in our Vancouver office with an office-centric hybrid schedule. The standard in-office days are Monday, Tuesday, and Thursday. Most Asanas have the option to work from home on Wednesdays. Working from home on Fridays depends on the type of work you do and the teams with which you partner. If you're interviewing for this role, your recruiter will share more about the in-office requirements.

What you’ll achieve

• Work closely with Product Managers and User Researchers (UXR) to understand the needs of our new customers in their first few minutes of interaction with Asana, employing data frameworks and methodologies to understand our user segments, visualize the new user funnel, identify levers for driving conversion revenue, and personalize the onboarding journey to ensure better adoption outcomes. 
• Act as the "Data Lead" in a triad with Product and Engineering stakeholders to identify multi-year growth opportunities and prioritize the roadmap.
• Design experiments that measure product progress, and own key performance metrics.
• Collaborate and mentor fellow Data Scientists in the team to research, identify and disseminate best practices across teams.
• Work in a high-performance, dynamic team with a strong focus on velocity and software quality and learn about the upcoming field of AI-Optimization and how LLMs can help boost Asana’s value proposition. 

About you

• 5-7 years of data science experience, with majority in growth-focused roles at B2B SaaS companies 
• Proven track record driving acquisition and activation for B2B SaaS products, with specific experience in top-of-funnel growth and new user acquisition.
• 0→1 builder mentality. You've demonstrated the ability to thrive in highly ambiguous environments where you're inventing new playbooks rather than executing existing ones. You're energized by pioneering work.
• Experience with AI/ML products, LLM APIs, or third-party platform integrations. Strong preference for candidates who've worked with conversational AI or built features integrating ChatGPT, Claude, or similar platforms.
• Strong analytical foundation with deep fluency in experimentation, A/B testing, and funnel optimization.
• Exceptional cross-functional leadership. You write crisply, tell clear stories, and can influence across product, engineering, design, partnerships, sales, and executive stakeholders. You bring clarity to ambiguity.
• Strategic business acumen to balance user experience with revenue objectives while translating emerging technology trends into actionable product strategy.
• Genuine AI enthusiasm. You're curious, adaptable, and genuinely excited about how LLMs are transforming software discovery and adoption.
• Expert in relational data modeling and SQL and fluent in at least one modern language useful for data processing (e.g. R, Python, or Scala).
• Familiarity with statistical methods including experimental design, regression, causal inference with observational data and time series modeling.
• Demonstrates curiosity about AI tools and emerging technologies, with a willingness to learn and leverage them to enhance productivity, collaboration, or decision-making

At Asana, we're committed to building teams that include a variety of backgrounds, perspectives, and skills, as this is critical to helping us achieve our mission. If you're interested in this role and don't meet every listed requirement, we still encourage you to apply.

What we’ll offer

Our comprehensive compensation package plays a big part in how we recognize you for the impact you have on our path to achieving our mission. We believe that compensation should be reflective of the value you create relative to the market value of your role. To ensure pay is fair and not impacted by biases, we're committed to looking at market value which is why we check ourselves and conduct a yearly pay equity audit. 

For this role, the estimated base salary range is between CAD 211,000-240,000. The actual base salary will vary based on various factors, including market and individual qualifications objectively assessed during the interview process. The listed range above is a guideline, and the base salary range for this role may be modified.

In addition to base salary, your compensation package may include additional components such as equity, sales incentive pay (for most sales roles), and benefits. If you're interviewing for this role, speak with your Talent Acquisition Partner to learn more about the total compensation and benefits for this role.

We strive to provide equitable and competitive benefits packages that support our employees worldwide and include:

• Mental health, wellness & fitness benefits
• Career coaching & support
• Inclusive family building benefits
• Long-term savings or retirement plans
• In-office culinary options to cater to your dietary preferences 

These are just some of the benefits we offer, and benefits may vary based on role, country, and local regulations. If you're interviewing for this role, speak with your Talent Acquisition Partner to learn more about the total compensation and benefits for this role.

#LI-Hybrid

Your role
As an Applied Scientist at Dialpad, you'll be a key driver within our AI team, conducting R&D to power the next generation of autonomous voice agents. While traditional NLP focuses on analyzing static text, your work will center on real-time, multimodal systems that can listen, reason, and take action during live customer interactions. A major focus of the team is advancing DialpadGPT, our proprietary LLM, specifically optimizing it to drive orchestrated agentic workflows and handle complex task execution. Beyond the technical skills, we are a team that values collaboration, continuous learning, and the application of diverse perspectives to solve complex problems. Collaboration will be key as you work alongside our engineering, design, and product teams to build groundbreaking agentic applications.

If you're passionate about agentic and multimodal AI and contributing to a team that's changing the face of business communications, you'll find yourself right at home with us.

This position reports to the Senior Manager of the NLP team and has the opportunity to be based in Vancouver, BC.

What you’ll do

• Research and develop state-of-the-art algorithms for autonomous voice agents, specifically focusing on real-time speech processing and reasoning loops.
• Advance DialpadGPT: Design and execute distributed training strategies to optimize our proprietary LLMs for agentic behaviors, including precise tool use, instruction following, and latency-constrained generation.
• Conduct rigorous evaluation and monitoring of model performances and troubleshoot issues with a keen understanding of resultant business impacts.
• Design and implement orchestration layers that effectively chain LLMs with external tools and APIs to solve complex customer problems autonomously.
• Work with large-scale multimodal datasets (text, audio) to improve model robustness and alignment.
• Collaborate with engineering, product, and design teams to deploy scalable, low-latency models and algorithms in production.
• Submit papers to top-tier academic conferences (ACL, EMNLP, NeurIPS) and contribute to the team’s research culture.

Skills you’ll bring

• Master’s or PhD degree in Computer Science, Machine Learning, Computational Linguistics, or a related quantitative field.
• 2+ years of industry experience in Machine Learning/NLP for Master’s degree holders, or 1+ years for PhD holders.
• Deep understanding of LLMs: Demonstrated experience with training, fine-tuning (PEFT/LoRA), and alignment techniques (RLHF/DPO) for specific domains or tasks.
• Experience with Agentic Systems: Familiarity with building autonomous agents, including concepts like tool use, function calling, reasoning chains (CoT), and memory management.
• Strong proficiency in Python and PyTorch, with the ability to write clean, production-ready research code.
• Research Track Record: A history of publishing in top-tier conferences (ACL, EMNLP, NeurIPS, ICASSP) is highly valued.
• Multimodal Awareness: Familiarity with speech technologies (ASR, TTS) or processing real-time audio streams is a strong plus.
• Ability to bridge the gap between research and product, translating complex technical concepts into business value.
• Familiarity with version control tools like Git for collaborative projects.

Job Description:

Robots can do amazing things - if they can see. That’s where you come in. We’re Apera AI. Our breakthrough 4D Vision™ systems turn blind robots into intelligent, adaptable workers. But that transformation doesn’t happen without great teams.

We are looking for a Senior Machine Learning and Computer Vision Applied Scientist with outstanding problem-solving skills to join our AI team. This is an in-person role based in our Vancouver office, where you will collaborate closely with a small group of ambitious engineers and applied scientists delivering the future of robotic perception. Your work will be both grounded in state-of-the-art research and applied to guiding industrial robots on factory floors around the world.

You will own projects end-to-end from literature review through prototyping, benchmarking, and scaling. This includes:

• Extending Apera’s industry best object detection, stereo depth estimation, and 6d pose estimation modules

• Integrating foundation models into our perception stack to improve generalization and few-shot/zero-shot capabilities

• Collaborating with the C++ application team to get models deployed and user experiences optimized

• Collaborating with the infrastructure team to train and manage data on AWS

• Tracking the latest publications in top computer vision and robotics venues

• Prototyping and then implementing production training and deployment, mainly in PyTorch

• Optimizing models for real-time deployment at the edge (~1 Hz, powerful NVIDIA GPU) to support high accuracy, high robustness robot guidance

• Engineering for industrial reliability of 99.9%

About you:

You are motivated, talented, hardworking and have an entrepreneurial spirit. You enjoy making large impact at your company. You enjoy solving challenging problems rooted in real-world physics using science, imagination, creativity, and persistence. 

What We’re Looking For:

• STEM bachelor's degree

• 5+ years of experience in using deep learning for CV

• 4+ years of experience in software development

• Bonus:

• • Master’s or PHD degree with focus on computer vision and machine learning

• • Experience in 3D geometry and related topics in graphics and deep learning

Why Apera?

• We offer a competitive compensation package, including a base salary range of CAD $140,000–$180,000 plus stock options, designed to recognize your expertise and align your success with the company’s growth.

• You’re building systems that support teams working on real, deployed AI and robotics solutions, not hypothetical future tech.

• A chance to do meaningful, foundational work in a company that values execution and clarity.

• A culture of curiosity: we experiment, learn fast, and share openly.

• Well-funded with a recent Series A to fuel ambitious product roadmaps and growth.

• Trusted by big-name automotive in TIER 1 suppliers.

• High-impact work with autonomy and clear paths to grow.

Join us to make robotics more accessible, predictable, and powerful.

Our co-op/intern experience is unique and designed to prepare you for professional success. Our ultimate goal is to give you the mentorship, training and work experience you need to start your career successfully!

As part of Visiers R&D organization, our data science team is responsible for the development of advanced numerical algorithms and statistical techniques that generate business insights from human resource data. Mentored by an experienced Data Scientist you will collaborate on projects that match both your interests and Visier business needs. This could be software engineering focused (e.g. enhancing our machine learning pipelines or prototyping of automated insight generation), or research focused (e.g. unveiling compelling insights into the workforce from our unique multi-million employee cross-customers data set).

What you'll be doing...

• Modelling the problem at hand, such that it directly solves underlying business problems
• Brainstorming to identify the correct data required to solve business problems
• Performing statistical analysis on data to build statistical/machine learning models
• Identifying the right metrics to measure the success of the models and projects
• Communicating and presenting your work to stakeholders across the organisation
• Conducting independently research, in order to gain domain knowledge and learn cutting-edge techniques

What you'll bring to the table...

• Strong understanding of statistics and how to apply scientific methods to data using algorithms
• Coding skills in Scala, Python or other relevant languages
• Attention to detail and big picture thinking
• Currently pursuing your Masters or PhD
• Knowledge in one of the following areas would be an advantage:
• Hypothesis testing
• Machine learning techniques
• Scientific analysis and knowledge generation

The base pay range for this position in Canada is $5,500k / month.

The compensation offered will be determined by factors such as relevant qualifications, experience, knowledge and skills. Many of our positions are eligible for additional types of compensation (e.g., commission plans, bonus, etc.) which our Talent Acquisition team will share with you if you interview for the role.

About impact.com
impact.com is the world’s leading commerce partnership marketing platform, transforming the way businesses grow by enabling them to discover, manage, and scale partnerships across the entire customer journey. From affiliates and influencers to content publishers, brand ambassadors, and customer advocates, impact.com empowers brands to drive trusted, performance-based growth through authentic relationships. Its award-winning products - Performance (affiliate), Creator (influencer), and Advocate (customer referral) - unify every type of partner into one integrated platform. As consumers increasingly rely on recommendations from people and communities they trust, impact.com helps brands show up where it matters most. Today, over 5,000 global brands - including Walmart, Uber, Shopify, Lenovo, L’Oréal, and Fanatics - rely on impact.com to power more than 350,000 partnerships that deliver measurable business results.

Your Role at impact.com:

We're seeking a Senior Data Scientist to serve as an embedded Data Scientist within our Programmatic Experience Group. You'll own the design and deployment of machine learning models that optimize yield, pricing, and inventory allocation at scale — sitting at the intersection of data science, platform engineering, and marketplace economics.

This is a high-craft, high-ownership individual contributor role. You'll work end-to-end: architecting the data pipelines that feed your models, engineering the features that drive performance, and deploying real-time inference systems that make decisions at speed. Your work directly determines how effectively Impact's programmatic marketplace balances advertiser performance with publisher monetization — making this one of the highest-leverage technical roles in the business.

You'll collaborate closely with Product, Data Science, and Programmatic Delivery Engine Engineering, but you operate with significant autonomy. You're expected to bring both the modeling rigor of a data scientist and the production instincts of an ML engineer — and to be genuinely excited about both.

What You'll Do:

Yield Optimization & Pricing Models

• Design and deploy ML models that optimize auction pricing, bid shading, floor price setting, and yield across Impact's programmatic inventory.
• Build and iterate on real-time pricing algorithms that balance short-term revenue efficiency with long-term publisher and advertiser health.
• Develop and maintain feedback loops that allow pricing models to adapt to shifting market conditions, inventory mix, and demand patterns.
• Quantify the revenue impact of pricing model improvements; communicate tradeoffs between yield maximization, fill rate, and partner ROI to stakeholders.

Inventory Allocation & Supply Optimization

• Own ML-driven inventory allocation logic: routing, pacing, and matching supply to demand across partner segments, deal types, and campaign objectives.
• Build models that forecast inventory availability, demand curves, and clearing prices to support proactive allocation decisions.
• Identify and address inefficiencies in inventory utilization — including unsold inventory, suboptimal deal matching, and allocation imbalances across the publisher base.

Data Architecture & Feature Engineering

• Design and own the data infrastructure that feeds programmatic models: event pipelines, feature stores, training datasets, and real-time feature serving.
• Engineer high-signal features from auction logs, bid stream data, user signals, contextual attributes, and historical performance — at the scale of programmatic data volumes.
• Build robust data pipelines with production-grade standards: reliability, observability, versioning, and efficient reprocessing.

Real-Time Inference & Production ML

• Deploy models to production real-time inference environments; own latency, reliability, and throughput requirements for auction-time decision-making.
• Build monitoring systems that track model performance, data drift, and system health in production; define alerting thresholds and retraining triggers.
• Partner with MLOps and Platform Engineering to ensure scalable, low-latency serving infrastructure meets SLOs under high-volume auction traffic.
• Own the full model lifecycle: training, evaluation, deployment, A/B testing, and iteration.

Experimentation & Performance Measurement

• Design and execute rigorous A/B and holdout experiments to measure the causal impact of model changes on yield, fill rate, advertiser performance, and publisher revenue.
• Build evaluation frameworks that go beyond offline metrics — validating model behavior in live auction environments where feedback signals are delayed or noisy.
• Translate experimental results into clear business narratives; present findings and recommendations to Product and business stakeholders.

Self-Learning Systems & Feedback Loops

• Research and implement adaptive, self-learning components within the programmatic stack — including contextual bandits, reinforcement learning signals, and online learning approaches where appropriate.
• Design feedback mechanisms that close the loop between auction outcomes, model updates, and system behavior; reduce reliance on manual tuning and rule-based overrides.
• Stay current with advances in programmatic ML, auction theory, and online optimization; evaluate applicability to Impact's specific marketplace dynamics.

Cross-Functional Collaboration

• Serve as the primary ML technical partner for the Rubicon product and engineering teams; translate business requirements into modeling approaches and communicate technical tradeoffs clearly.
• Collaborate with Data Science peers on shared infrastructure, modeling standards, and cross-domain feature reuse.
• Document models, architectures, and experimental findings to a standard that enables review, replication, and knowledge transfer across teams.

What You Bring:

Required

• Experience: 5+ years in data science, ML engineering, or quantitative research, with at least 2+ years building and deploying ML models in programmatic advertising, ad tech, marketplace optimization, or a closely related domain (e.g., real-time bidding, dynamic pricing, auction systems).
• Programmatic & marketplace depth: Demonstrated understanding of programmatic auction mechanics (RTB, header bidding, floor pricing, deal types, bid shading) and how ML can be applied to optimize outcomes across the supply-demand stack.
• Production ML engineering: Proven ability to take models from prototype to production independently — including real-time inference, monitoring, retraining pipelines, and SLO ownership.
• Data architecture: Experience designing and building data pipelines, feature stores, and training infrastructure for high-volume, low-latency ML systems.
• Technical skills:
• Strong Python and SQL; proficiency with ML libraries (scikit-learn, XGBoost, LightGBM, PyTorch/TensorFlow) and large-scale data tools (Spark, Kafka, or equivalent streaming/batch frameworks).
• Experience with real-time feature serving and low-latency model deployment (REST APIs, gRPC, or streaming inference).
• Familiarity with production ML workflows: model versioning, drift monitoring, A/B testing, evaluation, and retraining.
• Experience processing and modeling at programmatic data scale: high-cardinality auction logs, bid stream data, impression and click events.
• Experimentation rigor: Strong grasp of causal inference and experiment design in online, delayed-feedback environments (auction holdouts, switchback tests, variance reduction techniques).
• Communication: Ability to explain complex modeling decisions and tradeoffs to Product and business stakeholders; comfortable presenting in cross-functional forums.
• Education: Bachelor's in a quantitative field (CS, Statistics, Math, Engineering, Economics, or similar); Master's/PhD preferred.

Preferred / Nice to Have

• Direct experience with SSP, DSP, or exchange-side yield optimization — particularly floor price optimization, bid landscape modeling, or deal matching algorithms.
• Familiarity with auction theory (first-price vs. second-price dynamics, optimal reserve pricing, revenue equivalence) and its practical implications for programmatic ML.
• Experience with contextual bandits, multi-armed bandits, or reinforcement learning applied to real-time decisioning problems.
• Knowledge of online learning and adaptive algorithms in production environments with non-stationary data distributions.
• Familiarity with privacy-preserving ML techniques relevant to programmatic (differential privacy, federated learning, cookieless attribution modeling).
• Experience with GCP tools (BigQuery, Vertex AI, Dataflow, Pub/Sub) and/or Databricks/Spark for large-scale event processing and model training.
• Exposure to supply forecasting, inventory management, or capacity planning in programmatic or marketplace contexts.
• Familiarity with Impact's affiliate and partnership ecosystem, or prior experience at the intersection of performance marketing and programmatic delivery.

What Sets You Apart

• Marketplace intuition. You understand programmatic auctions not just as an engineer but as an economist — you think about incentive structures, equilibrium dynamics, and how model decisions ripple through the supply-demand stack.
• Full-stack ML ownership. You're as comfortable designing a feature store schema as you are tuning a gradient boosting model or debugging a latency spike in production. You own the whole chain.
• Feedback loop thinking. You don't just deploy models — you design the systems that make them smarter over time. You think about how today's decisions become tomorrow's training signal.
• Rigor under real-world constraints. You know how to run clean experiments in environments where feedback is delayed, data is noisy, and business pressures create tradeoffs. You don't let imperfect conditions become an excuse for imprecise thinking.
• Pragmatic delivery. You ship. You balance the perfect with the production-ready, iterate fast, and know when an MVP outperforms a six-month research project.
• Collaborative depth. You build genuine technical trust with engineering and product partners — not just by having good ideas, but by following through, communicating clearly, and making the integration easy.

Salary Range: $165,000 - $185,000 per year, plus an additional 5% variable annual bonus contingent on Company performance and eligible to receive a Restricted Stock Unit (RSU) grant.

*This is the pay range the Company believes is equitable for this position at the time of this posting. Consistent with applicable law, compensation will be determined based on the skills, qualifications, and experience of the applicant along with the requirements of the position, and the Company reserves the right to modify this pay range at any time.

Benefits and Perks: 

At impact.com, we believe that when you’re happy and fulfilled, you do your best work. That’s why we’ve built a benefits package that supports your well-being, growth, and work-life balance.

• Strong extended health benefits: Health & Prescription coverage, vision and dental care, virtual health care, out-of-country medical coverage
• Insurance coverage (life, short-term disability, long-term disability, and more)
• Health Care Spending Account
• Two different Employee Assistance Programs
• Flexible Working: Our Responsible PTO policy means you can take the time off you need to rest and recharge. We're committed to a positive work-life balance and provide a flexible environment that allows you to be happy and fulfilled in both your career and your personal life.
• Health and Wellness: Your well-being is a priority. Our mental health and wellness benefit includes up to 12 fully covered therapy/coaching sessions per year, with additional dependent coverage. We also offer a monthly gym reimbursement policy to support your physical health.
• A Stake in Our Growth: We offer Restricted Stock Units (RSUs) as part of our total compensation, giving you a stake in the company's growth with a 3-year vesting schedule, pending Board approval.
• Investing in Your Growth: We’re committed to your continuous learning. Take advantage of our free Coursera subscription and our PXA courses.
• Parental Support: We offer a generous parental leave policy, 26 weeks of fully paid leave for the primary caregiver and 13 weeks fully paid leave for the secondary caregiver.
• Technology Financial Support: We provide a technology stipend to help you set up your home office and a monthly allowance to cover your internet expenses. 

Note: Benefits may vary by location and are subject to local regulations.

impact.com is proud to be an equal-opportunity workplace. All employees and applicants for employment shall be given fair treatment and equal employment opportunity regardless of their race, ethnicity or ancestry, color or caste, religion or belief, age, sex (including gender identity, gender reassignment, sexual orientation, pregnancy/maternity), national origin, weight, neurodivergence, disability, marital and civil partnership status, caregiving status, veteran status, genetic information, political affiliation, or other prohibited non-merit factors.

#LI_Vancouver_Canada

Each of us cares about someone who will need medicines. That’s why our vision is to repeatedly beat the odds to deliver breakthrough medicines to patients that need them. We pursue truth and scientific rigour and have the courage to work at the edge of the unknown.

We are looking for an experienced, strategically minded Principal Scientist to join our expanding Non-Clinical Safety team based in Vancouver, Canada. You will be responsible for designing, planning, monitoring, and reporting of non-GLP and GLP toxicology studies and provide nonclinical safety support for early to late stage programs. 

How you might spend your days

• Leading the planning, design, execution and interpretation of nonclinical toxicology programs in support of IND, CTA and BLA submissions, including general toxicity and reproductive and developmental toxicology studies, in alignment with global regulatory expectations and program strategy
• Serving as the primary scientific interface with contract research organizations (CROs), providing strategic oversight during protocol development, study conduct, data interpretation, and report finalization to ensure timely, high-quality, and GLP-compliant delivery of nonclinical studies
• Representing the Nonclinical Safety function as a core member of cross-functional discovery and development program teams, contributing toxicology expertise to inform candidate selection, risk assessment, and overall program advancement
• Providing critical scientific assessment of toxicology data and communicating clear, actionable risk-benefit evaluations and recommendations to project teams and senior leadership, including potential implications for clinical development and regulatory strategy 
• Authoring and reviewing nonclinical safety sections of regulatory documents (INDs, CTAs, IBs, and BLAs), and contributing as a subject matter expert to global regulatory interactions and health authority responses
• Driving the development and evolution of integrated nonclinical safety strategies across AbCellera’s therapeutic portfolio, ensuring consistency, scientific rigor, and alignment with company objectives
• Maintaining scientific leadership by staying current with advances in toxicology science, methodologies, and evolving regulatory guidance, and proactively translating these insights into best practices for internal programs

We'd love to hear from you if

• You bring deep expertise in GLP-compliant nonclinical toxicology, including hands-on experience with US FDA 21 CFR Part 58, and a strong working knowledge of FDA, ICH, and EMA nonclinical regulatory guidance
• You have a proven track record of designing, overseeing, and interpreting non-GLP and GLP toxicology studies in support of discovery and development programs; experience with oncology and/or ADC programs is highly desirable
• You hold a PhD in Toxicology or a related field, with 8+ years of relevant industry experience supporting biologics development; candidates with a MSc degree and 12+ years of directly applicable experience will also be considered
• You demonstrate the ability to lead scientific discussions and influence decision-making within highly matrixed, cross-functional teams through clear, confident, and effective communication
• You possess excellent scientific writing skills, with experience authoring and reviewing toxicology reports and regulatory submission documents
• You exhibit strong organizational and prioritization skills, enabling effective management of multiple programs and timelines in a fast-paced environment
• You apply sound scientific judgment and critical problem-solving skills to assess complex datasets, identify risks, and propose strategic solutions
• You thrive in a dynamic, evolving environment, demonstrating flexibility, resilience, and a proactive approach to change
• You hold DABT accreditation (highly desirable, but not required)

What we offer

AbCellera’s hiring range for this role is CAD $134,000 - $168,000 annually, commensurate with your education and job-related knowledge, skills, and experience. In addition to base salary, we offer equity, annual bonus dependent on team and company performance, and a 6% (non-match) RRSP contribution. 

You will have a CAD $1,500 annual Active Lifestyle Allowance, annual vacation, professional development opportunities, and comprehensive health benefits. Scientific and technical mentorship is a priority. And you’ll find a strong sense of community and connections across AbCellera through our work, clubs, and socials.

About AbCellera

Creating medicines is the most important work we can do. 

We are a clinical-stage biotechnology company focused on discovering and developing antibody-based medicines in the areas of endocrinology, women’s health, immunology, and oncology. We have built a platform for advancing antibody drug programs from target to clinic, and we are using it to build our internal pipeline.

Today, our pipeline includes two drug candidates in clinical development, two preclinical development candidates (DCs) in Investigational New Drug (IND)-enabling activities, and more than 20 active discovery programs across multiple modalities and indications.

We believe that when tenacious people share a vision and work together, they can truly have a positive impact. That’s why we hire for character and intelligence, not just for CVs or experience. 

We look for people with drive and energy. People we trust. People who need to know their days are being well spent. That their work really matters. In the end, our success will be measured by the impact of our medicines.

To apply

Please submit your application through our website and refer to Job ID 23346 in your cover letter. We receive a large volume of applications and are only able to contact those who are selected for an interview. All communication from our Talent Discovery team will come from an @abcellera.com email address.

About The Team 

Cerebras builds wafer-scale AI processors—single chips delivering tens of PB/s of memory bandwidth and a dataflow architecture that accelerates at a granularity no multi-device system can match. The Advanced Technology Group (ATG) is Cerebras’ pathfinding organization. We work ahead of product to explore new architectures, demonstrate breakthrough performance on scientific and AI workloads, and shape the technical roadmap for future Cerebras hardware and software. Our work regularly appears at top-tier venues (Supercomputing, SIAM, IEEE, and NeurIPS) and directly influences the design of next-generation wafer-scale systems. 

About The Role 

Most AI research today is shaped by the constraints of existing hardware. This role starts from the other direction: what would you build if the architecture let you rethink the fundamentals? You will design and develop AI models and training methodologies on wafer-scale hardware, working at the level of optimization theory, model architecture, and statistical foundations rather than assembling existing components. 

The ATG sits at the intersection of AI, computational science, and computer architecture, and your work will draw on all three. You will collaborate closely with Cerebras’ ASIC, compiler, kernel, and AI teams as well as external partners at universities and national laboratories. 

What You Will Do 

• Design AI models and training methods from first principles, leveraging architectural properties of wafer-scale hardware that are unavailable on conventional platforms. 
• Investigate how techniques from computational science—numerical methods, PDE solvers, simulation—can inform and advance AI model design, and explore hybrid workflows that couple simulation and learning. 
• Develop a deep understanding of the hardware substrate and use it to guide algorithmic choices: model structure, optimization strategy, memory access patterns, numerical precision. 
• Publish findings and present at top-tier venues (NeurIPS, ICML, ICLR, etc.); represent Cerebras in the broader AI/ML research community. 
• Inform the design of future Cerebras hardware and software by identifying the computational patterns that matter most for next-generation AI workloads. 

What We Are Looking For 

• PhD in Machine Learning, Computer Science, Applied Mathematics, Statistics, Physics, or a related quantitative field preferred; exceptional candidates without a graduate degree who demonstrate equivalent depth through published research, significant open-source contributions, or a strong industry track record are encouraged to apply. 
• Mathematical maturity: comfort with the theory behind gradient methods, loss landscapes, generalization, and the relationship between model structure and data statistics. 
• Track record of published research at top-tier AI or computational science venues. 
• Proficiency in Python and PyTorch; comfort with C or other low-level languages is a strong signal. 
• Excellent communication and interpersonal skills: able to present complex technical material to both ML and systems audiences, and to collaborate effectively in a fast-paced, small-team environment. 

Why This Opportunity Is Exciting And Unique 

• You will have direct access to hardware that changes what’s algorithmically possible. Tens of PB/s of memory bandwidth and fine-grained dataflow execution open design spaces that don’t exist on GPU clusters. 
• You will work alongside researchers in computational science, computer architecture, and performance engineering. The synthesis across these fields is central to ATG’s approach. 
• Your research will influence silicon - ATG’s findings directly shape the design of future Cerebras chips and systems. 

We are hiring for multiple positions across experience levels. If this work resonates, we encourage you to apply. 

We're looking for a Scientist, Analytical Development to join Aspect's technical operations team. In this role, you'll be instrumental in developing, optimizing, and qualifying analytical methods that support our cutting-edge bioprinted tissue therapeutics. Reporting to a Head, Quality Control and Analytical Development, you'll play a crucial part in ensuring the quality and characterization of our innovative products as we advance toward clinical development.

Responsibilities 

• Design, execute, and optimize a variety of analytical methods (e.g.cell-based assays, bioanalytical and flow cytometry methods) for the characterization, release, and stability testing of raw materials, in-process samples, and final drug products.
• Participate in and execute experiments for the qualification and validation of analytical methods in accordance with phase-appropriate regulatory guidelines (e.g., ICH, FDA, Health Canada, EMA).
• Perform routine analytical testing as needed to support process development, product characterization, and early-stage stability studies.
• Accurately record, analyze, interpret, and present experimental data. Author and review technical reports, study protocols, and standard operating procedures (SOPs) in compliance with GxP principles.
• Identify and troubleshoot analytical method issues, propose solutions, and implement corrective actions.
• Work cross functionally with Process Development, Quality Control, Research & Development, and Manufacturing to support product development milestones and resolve analytical challenges.
• Perform routine maintenance and calibration of analytical instruments and ensure proper functioning.
• Adhere to and contribute to the development of robust analytical quality systems, ensuring data integrity, traceability, and compliance with internal and external regulations.

Qualifications & Experience

• Education & Experience: Bachelor's or Master's degree in a relevant scientific discipline with 3-5 years of relevant experience in analytical development within the biotechnology or pharmaceutical industry with hands-on experience in cell therapy, gene therapy, or combination products. 
• Analytical Expertise: Proven hands-on experience with a range of analytical techniques, such as flow cytometry, ELISA, and/or cell-based assays.
• GxP Knowledge: Familiarity with GxP principles (GLP, GMP) and an understanding of regulatory expectations for analytical method development, qualification, and validation for biologics or advanced therapies.
• Problem-Solver: You have a keen eye for detail and a methodical approach to troubleshooting analytical challenges.
• Innovation Mindset: You're eager to learn new techniques and contribute to the continuous improvement of analytical processes.

The hiring range for this role is $90,000 - $96,300, annually. Our pay scales are based on market data to ensure that compensation is competitive and fair. Offered salaries will be based on a combination of factors including, but not limited to, job-related knowledge, skills, education, and experience. For candidates who exceed role requirements, we are open to exploring above-range offers. Base salary is just one part of the overall compensation at Aspect, team members also receive equity, a comprehensive benefits package, and support for continuous learning and career progression.