We are looking for a Senior Data Scientist. You will shape the future of people-facing and business-facing products we build at Pinterest. Your expertise in quantitative modeling, experimentation and algorithms will be utilized to solve some of the most complex engineering challenges at the company. You will collaborate on a wide array of product and business problems with a diverse set of cross-functional partners across Product, Engineering, Design, Research, Product Analytics, Data Engineering and others. The results of your work will influence and uplevel our product development teams while introducing greater scientific rigor into the real world products serving hundreds of millions of pinners, creators, advertisers and merchants around the world.

What you’ll do

• Develop best practices for instrumentation and experimentation and communicate those to product engineering teams to help us fulfill our mission - to bring everyone the inspiration to create a life they love.
• Bring scientific rigor and statistical methods to the challenges of product creation, development and improvement with an appreciation for the behaviors of our Pinners.
• Build and prototype analysis pipelines iteratively to provide insights at scale while developing comprehensive knowledge of data structures and metrics, advocating for changes where needed for product development.
• Work cross-functionally to build and communicate key insights, and collaborate closely with product managers, engineers, designers, and researchers to help build the next experiences on Pinterest.
• Leverage AI to seek faster execution (i.e. draft, prototype, outline) and explore alternative options (i.e. iterate, compare approaches).
• Leverage AI to synthesize information (summarize, distill themes) and automate repeatable tasks (documentation, reporting, QA checks).

What we’re looking for

• • 5+ years of experience analyzing data in a fast-paced, data-driven environment with proven ability to apply scientific methods to solve real-world problems on web-scale data.
  • Extensive experience solving analytical problems using quantitative approaches including in the fields of Statistics, Machine Learning, Forecasting, Econometrics or other related fields.
  • Experience solving problems within digital advertising is preferred.
  • Familiarity with online experimentation and its pitfalls.
  • A scientifically and statistically rigorous approach to analysis and data.  You rely on statistically valid approaches to problems and have a well-tuned sense of skepticism, attention to detail and commitment to high-quality, results-oriented output.
  • Ability to manipulate large data sets with high dimensionality and complexity; fluency in SQL (or other database languages) and a scripting language (Python or R).
  • Excellent communication skills and ability to explain learnings to both technical and non-technical partners, including Product and Machine Learning teams.
  • A team player who’s able to partner with cross-functional leadership to quickly turn insights into actions.
  • Demonstrated ability to use AI to improve speed and quality in your day-to-day workflow for relevant outputs.
  • Strong track record of critical evaluation and verification of AI-assisted work (e.g., testing, source-checking, data validation, peer review).
  • High integrity and ownership: you protect sensitive data, avoid over-reliance on AI, and remain accountable for final decisions and deliverables.
  • Bachelor’s or Master’s degree in a relevant field such as Data Science, or equivalent experience.

This job posting is for an open vacancy. Please note that the company utilizes artificial intelligence to screen applicants for the positions.

Relocation Statement:

• This position is not eligible for relocation assistance. Visit our PinFlex page to learn more about our working model.

In-Office Requirement Statement:

We let the type of work you do guide the collaboration style. That means we're not always working in an office, but we continue to gather for key moments of collaboration and connection.

This role will need to be in the office for in-person collaboration 1-2 times per half and therefore can be situated anywhere in Ontario. 

#LI-HYBRID

#LI-CH1

We are looking for a Senior Staff Scientist – Fault-Tolerant Quantum Algorithms to help lead the technical development of highly differentiated quantum solutions that will bring value to society. As a Senior Staff Scientist – Fault-Tolerant Quantum Algorithms, you’ll guide a cross-functional team whose mandate is central to IonQ’s mission to solve the world’s most complex problems using the world’s best quantum computers.

As a technical leader in the field of fault-tolerant algorithms, you will help discover the next generation of quantum applications that will exceed state-of-the-art classical methods. You will be a core member of technical leadership in quantum algorithms, and you will drive research into new quantum algorithms and develop IP, computational resource models, long-term roadmaps, and end-to-end workflows that have the potential to disrupt the field of computing. You will also work closely with product, engineering, marketing, sales, operations, and external customers/partners to brainstorm new ideas, propose complex, multi-year initiatives and represent IonQ at high-visibility technical conferences (often all in a single day)!

Responsibilities: 

• Influence the quantum applications roadmap towards fault-tolerant quantum algorithms that will make a large scientific and commercial impact by leading the origination, execution, and optimization of novel, end-to-end quantum algorithms. Guide other team members towards this goal.
• Perform detailed resource analyses of quantum algorithms and perform SWOT analysis of FTQC approaches compared to NISQ and/or classical methods.
• Provide trusted expertise and leadership in FTQC algorithms and communicate the current state-of-the-art, scaling behaviors, trade offs, cross-over points, etc. to stakeholders across the company.
• Lead technical interactions across multi-disciplinary teams to identify, define and solve challenging real-world problems using IonQ trapped-ion quantum computers.
• Define, develop, and drive adoption of industry-leading benchmarking and resource estimation methodologies, metrics, and tools.
• Develop portfolio of foundational IP and high-impact-factor peer-reviewed publications; represent IonQ externally with customer/clients and at conferences.

You’d be a good fit with:

• PhD in physics, mathematics, computer science, or similar field, or comparable field or equivalent work experience + 5 years of professional experience in the quantum computing field
• 13+ years of professional experience or an equivalent combination of education and experience
• Demonstrated expertise in FTQC algorithms that can scale to millions of qubits, billions of gates with line-of-sight to end-customer value: active portfolio of invited talks, repos, licenses, publications and/or patents.
• Active participant in the FTQC algorithm community via, e.g., development of tools (libraries, simulators, compiler), metrics (costing, resource estimation, ROI), and/or community (economic development, standards)
• Relentless dedication to optimizing algorithmic performance (accuracy, time-to-solution) through elegant theoretical equations, as well as engineering optimization
• Mastery of key mathematical techniques used in quantum computing and quantum algorithm development, and a demonstrated ability to communicate scientific results clearly.

You’d be a great fit with: 

• 7+ years of professional work experience developing FT quantum algorithms that align with realistic industry problems such as computer-aided engineering, phase transitions, reaction modeling, cybersecurity, differential equations solving, simulation of physical systems, etc. 
• Deep expertise in quantum algorithms for relevant use cases. This could include quantum simulation (e.g., product formulas, qubitization, qDRIFT, etc.), quantum algorithms and primitives (e.g., block-encodings, LCU, QSP, QSVT, Gibbs sampling, quantum linear systems, etc.), and/or end-to-end fault-tolerant quantum algorithms as applied to detailed use cases.
• Demonstrated expertise in Python and Qiskit or similar quantum SDK; working knowledge of C++.
• Experience proposing, winning, and executing on consultative (paid) contracts; government contracting or defense contracting experience a plus
• Experience commercializing end-to-end software utilizing hybrid computing e.g. CPU + GPU + QPU, Edge, Cloud, etc. Knowledge of CI/CD a plus.

Location: This position can work onsite or hybrid from one of our offices (College Park, MD, Bothell, WA, Toronto, Canada, Gothenburg, Sweden) or fully remote in the US
Travel: 10% domestic and international
Job ID:  1254

The approximate base salary range for this position is $192,979 - $252,659. The total compensation package includes base, bonus, and equity.

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’s Data Science Team builds mathematical models underpinning the platform’s core services. Compared to other technology companies of a similar size, the set of problems that we tackle is incredibly diverse. They cut across optimization, prediction, modeling, inference, transportation, and mapping. We are hiring motivated experts in each of these fields. We're looking for someone who is passionate about solving mathematical problems with data, and are excited about working in a fast-paced, innovative and collegial environment.

You will report into a Science Manager.

Responsibilities:

• Partner with Engineers, Product Managers, and Business Partners to frame problems, both mathematically and within the business context.
• Perform exploratory data analysis to gain a deeper understanding of the problem
• Construct and fit statistical, machine learning, or optimization models
• Write production modeling code; collaborate with Software Engineers to implement algorithms in production
• Design and run both simulated and live traffic experiments
• Analyze experimental and observational data; communicate findings; facilitate launch decisions

Experience:

• Ph.D. in Statistics, Operations Research, Mathematics, Computer Science, or other quantitative fields
• 2+ years professional experience in a technology companies
• Passion for solving unstructured and non-standard mathematical problems
• End-to-end experience with data, including querying, aggregation, analysis, and visualization
• Proficiency with Python, or another interpreted programming language like R or Matlab
• Willingness to collaborate and communicate with others to solve a problem

Benefits:

• Extended health and dental coverage options, along with life insurance and disability benefits
• Mental health benefits
• Family building benefits
• Child care and pet benefits
• Access to a Lyft funded Health Care Savings Account
• RRSP plan with company match to help save for your future
• In addition to provincial observed holidays, salaried team members are covered under Lyft's flexible paid time off policy. The policy allows team members to take off as much time as they need (with manager approval). Hourly team members get 15 days paid time off, with an additional day for each year of service 
• Lyft is proud to support new parents with 18 weeks of paid time off, designed as a top-up plan to complement provincial programs. Biological, adoptive, and foster parents are all eligible.
• Subsidized commuter benefits and Lyft ride credits

Lyft is committed to creating an inclusive workforce that fosters belonging. Lyft believes that every person has a right to equal employment opportunities without discrimination because of race, ancestry, place of origin, colour, ethnic origin, citizenship, creed, sex, sexual orientation, gender identity, gender expression, age, marital status, family status, disability, pardoned record of offences, or any other basis protected by applicable law or by Company policy. Lyft also strives for a healthy and safe workplace and strictly prohibits harassment of any kind.  Accommodation for persons with disabilities will be provided upon request in accordance with applicable law during the application and hiring process. Please contact your recruiter if you wish to make such a request.

Lyft highly values having employees working in-office to foster a collaborative work environment and company culture. This role will be in-office on a hybrid schedule — Team Members will be expected to work in the office at least 3 days per week, including on Mondays, Wednesdays, and Thursdays. Lyft considers working in the office at least 3 days per week to be an essential function of this hybrid role. Your recruiter can share more information about the various in-office perks Lyft offers. Additionally, hybrid roles have the flexibility to work from anywhere for up to 4 weeks per year. #Hybrid

The expected base pay range for this position in the Toronto area is CAD $108,000 - CAD $135,000, not inclusive of potential equity offering, bonus or benefits. Salary ranges are dependent on a variety of factors, including qualifications, experience and geographic location. Your recruiter can share more information about the salary range specific to your working location and other factors during the hiring process.

Lyft may use artificial intelligence to screen applicants, however, Lyft employees make the ultimate selection and hiring decisions.

This job fills an existing vacancy.

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.

As a Data Scientist on the Mapping team, you will collaborate with our world class team of engineers, product managers, and designers to grow and improve the quality of recommended routes and accuracy of our travel time estimations. We're looking for a passionate, driven Data Scientist who is excited to dive into our spatial data and build a best-in-class mapping product that provides safe, efficient, and seamless navigation for our rideshare drivers.

Data Science is at the heart of Lyft’s products and decision-making. You will leverage data and rigorous, analytical thinking to shape our mapping products and make business decisions that put our customers first. This will involve identifying and scoping opportunities, shaping priorities, recommending technical solutions, designing experiments, and measuring the impact of new features. You will help us solve some of the most impactful problems in mapping, including:

• How do we improve the quality of our map data in order to improve our recommendations?
• How do we benchmark and measure the success of our services?
• How do we validate features of the real world that affect our routing algorithms?
• Are we meeting our travel estimation promises to our customers?

Responsibilities

• Leverage data and analytic frameworks to identify opportunities for growth and efficiency
• Partner with product managers, engineers, and operators to translate analytical insights into decisions and action, and implement products to drive business goals
• Define and implement decision frameworks, measurement strategies, and scientific methodologies that bring consistency and rigor to business decisions and forecasts, balancing opportunity and uncertainty
• Deliver integrated, high-quality analytical outputs spanning multiple projects while navigating ambiguity, cross-team dependencies, and open-ended scope
• Design and analyze online experiments; communicate results and act on launch decisions
• Establish metrics that measure the health of our products, as well as rider and driver experience
• Identify and drive impact and alignment, shaping product and business strategy through data-centric presentations 
• Contribute to the Science community (hiring, onboarding, documentation, knowledge-sharing, tooling improvements), helping make Decision Science at Lyft more effective and scalable

Experiences

• Degree in a quantitative field such as statistics, economics, applied math, operations research or engineering (advanced degrees preferred), or relevant work experience
• 3+ years experience in a data science role or analytics role
• Demonstrated ability to own multi-project analytical scopes with ambiguous problem definitions and cross-functional integration
• End-to-end experience with data, including querying, aggregation, analysis, and visualization
• Proficiency in SQL - able to write structured and efficient queries on large data sets
• Experience in programming, especially with data science and visualization libraries in Python or R, and machine learning libraries such as PyTorch, TensorFlow, Keras
• Experience in online experimentation and statistical analysis, and communicating results and recommendations to senior stakeholders
• Strong communication, critical thinking, and prioritization skills, including the ability to challenge assumptions, propose alternatives, and balance short-term vs. long-term tradeoffs
• Experience in applying machine learning techniques is a plus (e.g. reinforcement learning) to solve customer problems (e.g. personalization, segmentation)
• Expertise in metric design, causal analysis, behavioral analytics, decision frameworks and measurement strategy is a plus
• Experience working with ETL pipelines a plus

Benefits:

• Extended health and dental coverage options, along with life insurance and disability benefits
• Mental health benefits
• Family building benefits
• Child care and pet benefits
• Access to a Lyft funded Health Care Savings Account
• RRSP plan with company match to help save for your future
• In addition to provincial observed holidays, salaried team members are covered under Lyft's flexible paid time off policy. The policy allows team members to take off as much time as they need (with manager approval). Hourly team members get 15 days paid time off, with an additional day for each year of service 
• Lyft is proud to support new parents with 18 weeks of paid time off, designed as a top-up plan to complement provincial programs. Biological, adoptive, and foster parents are all eligible.
• Subsidized commuter benefits and Lyft ride credits

Lyft is committed to creating an inclusive workforce that fosters belonging. Lyft believes that every person has a right to equal employment opportunities without discrimination because of race, ancestry, place of origin, colour, ethnic origin, citizenship, creed, sex, sexual orientation, gender identity, gender expression, age, marital status, family status, disability, pardoned record of offences, or any other basis protected by applicable law or by Company policy. Lyft also strives for a healthy and safe workplace and strictly prohibits harassment of any kind.  Accommodation for persons with disabilities will be provided upon request in accordance with applicable law during the application and hiring process. Please contact your recruiter if you wish to make such a request.

Lyft highly values having employees working in-office to foster a collaborative work environment and company culture. This role will be in-office on a hybrid schedule — Team Members will be expected to work in the office at least 3 days per week, including on Mondays, Wednesdays, and Thursdays. Lyft considers working in the office at least 3 days per week to be an essential function of this hybrid role. Your recruiter can share more information about the various in-office perks Lyft offers. Additionally, hybrid roles have the flexibility to work from anywhere for up to 4 weeks per year. #Hybrid

The expected base pay range for this position in the Toronto area is $108,000 - $135,000, not inclusive of potential equity offering, bonus or benefits. Salary ranges are dependent on a variety of factors, including qualifications, experience and geographic location. Your recruiter can share more information about the salary range specific to your working location and other factors during the hiring process.

Lyft may use artificial intelligence to screen applicants, however, Lyft employees make the ultimate selection and hiring decisions.

This job fills an existing vacancy.

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 & Customer Care (SCC) organization manages over 1.7 million monthly customer interactions and is responsible for ensuring the trust and safety of our riders and drivers. We work every day to build a trusted community, foster safe interactions, manage risky situations, and deliver best-in-class support. As part of this team, you will play a critical role in making transportation safer for all.

We are looking for an experienced and highly motivated Data Scientist to join the Community Safety Data team and lead key initiatives that enhance the safety of Lyft’s community. You’ll work cross-functionally with product management, engineering, design, legal, research, and operations teams to build impactful safety features, models, and systems. This high-impact role requires deep customer empathy, insatiable curiosity to uncover platform risks; and competencies to explore large datasets, develop statistical models, and design data-driven strategies for products that provide safe and engaging experiences for customers.

You’ll report to the Director of Data Science for the SCC org.

Responsibilities:

• Leverage data and analytical frameworks to identify opportunities for improving community trust and safety
• Partner with product managers, engineers, designers, marketers, and operators to translate insights into scalable, safety-forward decisions
• Design and analyze online experiments; interpret and communicate results to influence product launch decisions
• Build and monitor key metrics that reflect rider and driver safety, product health, and policy compliance
• Develop rigorous measurement strategies to evaluate the effectiveness of safety features, interventions, and detection systems
• Drive proactive risk identification and continuous improvement through analysis, experimentation, and iteration
• Mentored junior data scientists by providing guidance, feedback, and support to accelerate their technical and soft skill growth and impact.

Experience:

• Degree in a quantitative field such as Statistics, Economics, Applied Mathematics, Operations Research, or Engineering (advanced degrees preferred), or equivalent professional experience
• 3+ years of industry experience in data science or product analytics roles
• Proficiency in SQL with ability to write efficient queries on large, complex datasets
• Experience programming in Python or R, especially for data analysis, visualization, and modeling
• Strong foundation in statistical analysis and experimentation, including A/B testing design and/or Causal Inference techniques
• Excellent written and verbal communication skills with ability to influence cross-functional partners and executives, and translate data into compelling stories
• Self-starter with a curious mindset and a strong sense of ownership
• Ability to combine business intuition with the application of advanced solutions
• A passion for keeping up with the latest ongoings in Data Science and Machine Learning communities, and an obsession for data quality
• Prior experience in Trust & Safety, or Platform Integrity domains is a plus

Benefits:

• Extended health and dental coverage options, along with life insurance and disability benefits
• Mental health benefits
• Family building benefits
• Child care and pet benefits
• Access to a Lyft funded Health Care Savings Account
• RRSP plan with company match to help save for your future
• In addition to provincial observed holidays, salaried team members are covered under Lyft's flexible paid time off policy. The policy allows team members to take off as much time as they need (with manager approval). Hourly team members get 15 days paid time off, with an additional day for each year of service 
• Lyft is proud to support new parents with 18 weeks of paid time off, designed as a top-up plan to complement provincial programs. Biological, adoptive, and foster parents are all eligible.
• Subsidized commuter benefits and Lyft ride credits

Lyft is committed to creating an inclusive workforce that fosters belonging. Lyft believes that every person has a right to equal employment opportunities without discrimination because of race, ancestry, place of origin, colour, ethnic origin, citizenship, creed, sex, sexual orientation, gender identity, gender expression, age, marital status, family status, disability, pardoned record of offences, or any other basis protected by applicable law or by Company policy. Lyft also strives for a healthy and safe workplace and strictly prohibits harassment of any kind.  Accommodation for persons with disabilities will be provided upon request in accordance with applicable law during the application and hiring process. Please contact your recruiter if you wish to make such a request.

Lyft highly values having employees working in-office to foster a collaborative work environment and company culture. This role will be in-office on a hybrid schedule — Team Members will be expected to work in the office at least 3 days per week, including on Mondays, Wednesdays, and Thursdays. Lyft considers working in the office at least 3 days per week to be an essential function of this hybrid role. Your recruiter can share more information about the various in-office perks Lyft offers. Additionally, hybrid roles have the flexibility to work from anywhere for up to 4 weeks per year. #Hybrid

The expected base pay range for this position in the Toronto area is CAD $108000-$135,000, not inclusive of potential equity offering, bonus or benefits. Salary ranges are dependent on a variety of factors, including qualifications, experience and geographic location. Your recruiter can share more information about the salary range specific to your working location and other factors during the hiring process.

Lyft may use artificial intelligence to screen applicants, however, Lyft employees make the ultimate selection and hiring decisions.

This job fills an existing vacancy.

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, recommending and implementing technical solutions, designing experiments, shaping team priorities, and measuring the impact of new features.

The Verticals team encompasses 3 critical and unique products / marketplaces within Lyft: airports, scheduled rides, and events. 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 experiences and have unique considerations and dynamics. Scheduled rides allow riders to book a ride in advance with high reliability, and enable drivers to add structure to their work schedule. Lastly, events such as concerts or sporting games require similar considerations of special operations to ensure a seamless experience for both riders and drivers. 

As a Data Scientist on the Verticals team, you will collaborate with engineering, product, design, and operations 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:

• How can we efficiently match riders and drivers together in these unique marketplaces, to minimize ETAs and improve the driver experience? 
• Are we able to forecast ride demand and implement driver guidance to ensure riders can rely on Lyft for an event ride?
• What is the most helpful way to display ride information to drivers so they can make informed decisions?
• What rider segments should we target with ride incentives to grow our marketshare for these verticals? 

Responsibilities:

• Construct and fit statistical or optimization models to make production decisions such as changes to how we match riders and drivers; focusing on model proposal and offline model development 
• Leverage data and analytic frameworks to identify opportunities for growth and efficiency, recommending technical solutions to drive business impact 
• Design and analyze online experiments, including communicating results, acting on launch decisions, and recommending next steps based on learnings
• Partner with product managers, engineers, marketers, designers, and operators to translate data insights into decisions and action
• Develop analytical frameworks to monitor business and product performance, leveraging experiments and causal inference
• Establish metrics that measure the health of our products, the business, as well as the driver experience

Experience 

• Degree in a quantitative field such as statistics, economics, applied math, operations research or engineering (advanced degrees preferred), or relevant work experience
• 3+ years of industry experience in a data science, analytics, or management consulting role
• Proficiency in SQL and Python
• Ability to perform technical experiments, including user split, time split, and region split
• End-to-end experience with data, including querying, aggregation, analysis, and visualization
• Ability to manage, influence, negotiate, and inspire others in a fast-moving environment
• Strong oral and written communication skills, and ability to collaborate with cross-functional partners

Benefits:

• Extended health and dental coverage options, along with life insurance and disability benefits
• Mental health benefits
• Family building benefits
• Child care and pet benefits
• Access to a Lyft funded Health Care Savings Account
• RRSP plan with company match to help save for your future
• In addition to provincial observed holidays, salaried team members are covered under Lyft's flexible paid time off policy. The policy allows team members to take off as much time as they need (with manager approval). Hourly team members get 15 days paid time off, with an additional day for each year of service 
• Lyft is proud to support new parents with 18 weeks of paid time off, designed as a top-up plan to complement provincial programs. Biological, adoptive, and foster parents are all eligible.
• Subsidized commuter benefits and Lyft ride credits

Lyft is committed to creating an inclusive workforce that fosters belonging. Lyft believes that every person has a right to equal employment opportunities without discrimination because of race, ancestry, place of origin, colour, ethnic origin, citizenship, creed, sex, sexual orientation, gender identity, gender expression, age, marital status, family status, disability, pardoned record of offences, or any other basis protected by applicable law or by Company policy. Lyft also strives for a healthy and safe workplace and strictly prohibits harassment of any kind.  Accommodation for persons with disabilities will be provided upon request in accordance with applicable law during the application and hiring process. Please contact your recruiter if you wish to make such a request.

Lyft highly values having employees working in-office to foster a collaborative work environment and company culture. This role will be in-office on a hybrid schedule — Team Members will be expected to work in the office at least 3 days per week, including on Mondays, Wednesdays, and Thursdays. Lyft considers working in the office at least 3 days per week to be an essential function of this hybrid role. Your recruiter can share more information about the various in-office perks Lyft offers. Additionally, hybrid roles have the flexibility to work from anywhere for up to 4 weeks per year. #Hybrid

The expected base pay range for this position in the Toronto area is CAD $108,000 - CAD $135,000, not inclusive of potential equity offering, bonus or benefits. Salary ranges are dependent on a variety of factors, including qualifications, experience and geographic location. Your recruiter can share more information about the salary range specific to your working location and other factors during the hiring process.

Lyft may use artificial intelligence to screen applicants, however, Lyft employees make the ultimate selection and hiring decisions.

This job fills an existing vacancy.

Upwork Inc.’s (Nasdaq: UPWK) family of companies connects businesses with global, AI-enabled talent across every contingent work type including freelance, fractional, and payrolled. This portfolio includes the Upwork Marketplace, which connects businesses with on-demand access to highly skilled talent across the globe, and Lifted, which provides a purpose-built solution for enterprise organizations to source, contract, manage, and pay talent across the full spectrum of contingent work. From Fortune 100 enterprises to entrepreneurs, businesses rely on Upwork Inc. to find and hire expert talent, leverage AI-powered work solutions, and drive business transformation. With access to professionals spanning more than 10,000 skills across AI & machine learning, software development, sales & marketing, customer support, finance & accounting, and more, the Upwork family of companies enables businesses of all sizes to scale, innovate, and transform their workforces for the age of AI and beyond.

Since its founding, Upwork Inc. has facilitated more than $30 billion in total transactions and services as it fulfills its purpose to create opportunity in every era of work. Learn more about the Upwork Marketplace at Upwork.com and follow us on LinkedIn, Facebook, Instagram, TikTok, and X; and learn more about Lifted at Go-Lifted and follow on LinkedIn.

Sr. Lead AI Research Scientist, AI Evaluation and Reliability

The AI Foundations team leads core research and development across the training, evaluation, and deployment of AI systems that power Uma, Upwork’s flagship AI model, and other customer-facing generative AI capabilities. As a Sr. Lead AI Research Scientist focused on AI Evaluation and Reliability, you will drive high-impact research initiatives that improve the trustworthiness, robustness, and real-world performance of AI systems operating at marketplace scale.

At the Sr. Lead level, this role combines deep technical expertise with cross-functional leadership. You will identify and lead research efforts that address systemic reliability challenges, partner closely with engineering and product teams to translate research into production outcomes, and help shape how Upwork evaluates AI performance in real work scenarios. Your work will support AI systems embedded in retrieval-based workflows, agentic architectures, and human plus AI collaboration patterns, while contributing to Upwork’s broader AI research strategy and external presence.

Responsibilities:

• Lead applied research initiatives focused on AI evaluation, reliability, and robustness, defining success metrics tied to customer impact and production readiness.

• Design and validate methods to measure and mitigate AI reliability risks, including uncertainty estimation, hallucination detection, and identification of model failure modes.

• Partner cross-functionally with engineering, data science, and product teams to integrate research outcomes into customer-facing AI systems and workflows.

• Own research projects end to end, from problem framing and hypothesis development through experimentation, prototyping, and synthesis of results.

• Influence technical direction across teams by surfacing insights, proposing scalable solutions, and aligning stakeholders on priorities and tradeoffs.

• Mentor researchers and engineers through technical guidance, feedback, and collaborative leadership on shared initiatives.

• Contribute to Upwork’s external research footprint through publications, presentations, and engagement with the broader AI research community.

What it takes to catch our eye:

• Proven experience leading applied AI research that balances scientific rigor with real-world deployment constraints and business impact.

• A strong record of research contribution through publications, internal innovation, or demonstrable influence on production AI systems.

• Deep proficiency with Python and modern deep learning frameworks such as PyTorch, with hands-on experience evaluating and improving large-scale models.

• An adaptive approach to integrating AI tools into research and development workflows to accelerate experimentation, improve evaluation quality, and share best practices with others.

• A collaborative, growth-oriented mindset with the ability to mentor peers, communicate complex ideas clearly, and thrive in a fast-evolving, bottom-up environment.
  
  

Come change how the world works.

Upwork is establishing an operational hub in Toronto, Canada. The new office is expected to be fully operational by Q4 2026. This role will require 3 days in office once we have an office open.

This position will initially be employed through a partner to ensure a seamless hiring process while we establish the hub. Once the hub is established, there may be opportunities to transition to employment with Upwork, depending on business needs and other requirements. While employed by the partner, you’ll work as part of Upwork’s team, with access to our resources, culture, and growth opportunities.

Our partner will offer competitive benefits. When Upwork’s hub is established, we will be excited to offer employment and benefits directly as business needs require. 

Upwork is committed to building a diverse, inclusive, and equitable workforce. Employment decisions are made without regard to race, color, religion, gender, sexual orientation, gender identity, national origin, disability, or any other status protected by applicable law.

We use BrightHire, an AI-enabled tool, to record interviews and summarize interview transcripts. The tool allows the interviewer to focus on the discussion and does not score or evaluate candidates or make recommendations. The interview transcripts are reviewed, and decisions are only made by humans. Candidates who prefer not to have their interview recorded through BrightHire can opt out when the interview is scheduled.

To learn more about how Upwork processes and protects your personal information as part of the application process, please review our Global Job Applicant Privacy Notice and the Applicant Privacy Addendum (Canada).

Who we are

About Stripe

Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world’s largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone’s reach while doing the most important work of your career.

About the team

Our Data Science team partners deeply with teams across Stripe to ensure that our users, our products, and our business have the models, data products, and insights needed to make decisions and grow responsibly. We’re looking for data scientists with a passion for analyzing data, building machine learning and statistical models, and running experiments to drive impact.  Our work is broad and varied, influencing how our products work (e.g. understanding user needs, preventing fraud, or optimizing charge flows), how our business works (forecasting key outcomes, managing liquidity, quantifying risk exposure), how our go-to-market motions operate (designing growth experiments, optimizing marketing investments, refining sales processes, and estimating causal effects), and everything in between. We have a variety of Data Science roles and teams across Stripe and will seek to align you to the most relevant team based on your background.

What you’ll do

About the internship experience

Our internship program provides the opportunity to work on meaningful business initiatives that will grow the GDP of the internet. Through the internship, you will work with many systems and technologies, gain experience in working with large datasets and analytical methodologies/tools to help us better understand our users and build better products. 

Each intern has a dedicated mentor, and every intern project is part of the team's roadmap that will directly contribute to Stripe's mission. As you collaborate with industry experts on initiatives that expand global commerce, you will develop a strong first-hand understanding of the role analytics plays in steering business strategy and results.

We're not just focused on your immediate contributions; we're invested in your growth. Stripe sees this internship as an opportunity to grow your technical expertise and facilitate personal development, preparing you for a career in the tech industry.

Responsibilities

You will:

• Partner closely with Data Scientists, Data Analysts, and business partners to drive business impact through rigorous analytical solutions
• Apply machine learning, causal inference, or advanced analytics on large datasets to: i) measure results and outcomes, ii) identify causal impact and attribution, iii) predict the future performance of users or products, to drive business success
• Influence business actions and strategy by developing actionable insights through metrics and dashboards.
• Drive the collection of new data and the refinement of existing data sources.
• Learn quickly by asking great questions, finding how to work with your mentor and teammates effectively, and communicating the status of your work clearly
• Present your work to the Data Science team, partner teams, and fellow interns

Who you are

Minimum requirements

We’re looking for someone who has:

• Enrolled in a quantitative PhD program (e.g. Data Science, Statistics, Economics, Mathematics, etc.) with the expectation of graduating in winter 2026 or spring/summer 2027
• Experience with a scientific computing language (such as Python, R, etc) and SQL. We believe new programming languages can be learned if the fundamentals and general knowledge are present!
• Knowledge and hands-on experience in several of the following areas: machine learning, statistics, optimization, product analytics, causal inference, and/or experimentation
• Experience communicating and collaborating with multidisciplinary stakeholders in a team environment

Preferred qualifications

You also likely have:

• Experience writing and debugging data pipelines
• Demonstrated ability to evaluate and receive feedback from mentors, peers, and stakeholders via experience from previous internships or other multi-person projects
• Ability to learn new systems and form an understanding of those systems, through independent research and working with a mentor and subject matter experts

** This role is not eligible for hire in the United States - we are hiring only in Toronto, Ontario, Canada for summer 2026.

About the Role

What You'll Need

• Experience developing quantitative models to support real-world decision-making under uncertainty
• Strong coding skills in Python, with the ability to move beyond prototyping and implement production-quality scientific code
• Experience with one or more of the following: causal inference, Bayesian modeling, structural modeling, demand forecasting, pricing science, or mathematical optimization
• Comfort working with messy, high-dimensional real-world data and translating ambiguous business problems into rigorous modeling approaches
• Advanced degree (MS or PhD preferred) in statistics, mathematics, economics, operations research, computer science, or another quantitative discipline
• Strong communication and collaboration skills — you’re comfortable working with cross-functional stakeholders and can communicate technical ideas clearly

Nice to Have

What You'll Do

Compensation

About Clutch:

Clutch is Canada’s largest online used car retailer, delivering a seamless, hassle-free car-buying experience to drivers everywhere. Customers can browse hundreds of cars from the comfort of their home, get the right one delivered to their door, and enjoy peace of mind with our 10-Day Money-Back Guarantee… and that’s just the beginning.

Named one of Canada’s top growing Companies two years in a row and also awarded a spot on LinkedIn’s Top Canadian Startups list, we’re looking to add curious, hard-working, and driven individuals to our growing team.

Headquartered in Toronto, Clutch was founded in 2017. Clutch is backed by a number of world-class investors, including Canaan, BrandProject, Real Ventures, D1 Capital, and Upper90. To learn more, visit clutch.ca.

About the role:

Clutch is hiring a Staff Data Scientist to lead major improvements to our pricing algorithms and applied machine learning systems.

This is a high-ownership role for someone who thrives in ambiguity, can go deep on research and modeling, and has a track record of deploying ML to production with measurable business impact. You’ll work on ML systems that already drive real outcomes - including pricing models that purchase >$1M of vehicles per day with no human intervention - with significant opportunity to take them to the next level as we scale.

You’ll join a small, high-leverage data team where your work will be visible, measurable, and business-critical, with the chance to expand into additional high-impact ML domains like lending, logistics optimization, fraud detection, and recommendations. In this role, you’ll own problem areas end-to-end from identifying opportunities and shaping the approach, to shipping production models and driving measurable improvements in margin and conversion.

What you'll do:

• Own and drive improvements to Clutch’s pricing algorithms, balancing margin, conversion, and customer experience.
• Deep-dive into market and vehicle data to identify the key relationships between vehicle attributes, market dynamics, and pricing outcomes.
• Build, validate, and deploy ML models and algorithms into production — and iterate quickly based on real-world performance.
• Lead feature engineering, model evaluation, and experimentation design.
• Partner with Product, Engineering, Strategy & Ops, Sell-To-Clutch & Retail to prioritize the highest-impact opportunities.
• Contribute to additional applied ML domains as needed, including:
• Financing / lending decisioning
• Fraud detection
• Search and discovery optimization
• Vehicle recommendations / personalization

What we’re looking for:

• 8+ Years of Experience: A proven track record as a Data Scientist, with a history of delivering measurable business impact through machine learning.
• 0-to-1 Strategic Autonomy: Proven ability to navigate high-ambiguity environments. You own the roadmap by evaluating the data, identifying untapped opportunities, and formulating your own research theories.
• End-to-End Technical Ownership: Deep Python proficiency with the ability to own the entire lifecycle: from raw data exploration and feature engineering to model architecture and production deployment.
• Production-Grade ML: Strong experience building and deploying traditional ML algorithms into live environments, ensuring they are robust, scalable, and maintainable.
• Foundational Rigor: Strong statistical fundamentals and a disciplined approach to validation. You ensure that every model is built on a foundation of sound logic and clean data, maintaining high standards for accuracy and reliability without external oversight.
• Excellent Communication: Able to bridge the gap between complex technical findings and business ROI. You can distill "black box" complexity into clear trade-offs and actionable recommendations for business leaders.

About the Role

We’re looking for an Applied Scientist (ALL LEVELS) to push the boundaries of applied machine learning and AI at Opendoor. While this role will have a significant impact on our valuation systems — ensuring we provide the most accurate and transparent pricing possible — the scope goes well beyond pricing. You’ll work across a range of challenging ML problems, from multi-modal modeling to operational optimization, helping us rethink how we use structured and unstructured data to make better decisions for our customers.

What You'll Need

• Strong software engineering and coding skills in Python, with experience contributing to production codebases
  
  
• Experience developing and deploying ML models end-to-end — from research and prototyping to implementation in production systems
  
  
• Hands-on experience with deep learning architectures, including ConvNets, Transformers, or similar
  
  
• Advanced degree (MS or PhD) in computer science, statistics, mathematics, or a related quantitative field
  
  
• Solid foundation in statistics and experimental design
  
  
• Strong communication and collaboration skills — you’re comfortable working with cross-functional stakeholders and can communicate technical ideas clearly
  
  

Nice to Have

• Familiarity with Pyspark and distributed data processing
  
  
• Background in search, recommendation systems, or personalization
  
  
• Experience working with large language models (LLMs) or vision-language models (VLMs)
  
  
• A genuine interest in real estate — no prior experience required, but you'll engage deeply with housing data
  
  

What You'll Do

• Design and deploy architectural improvements to our deep neural network (DNN)-based home valuation models
  
  
• Build interpretable ML models that can help us explain pricing decisions to customers
  
  
• Incorporate unstructured data — like images, videos, or text — into our forecasting and valuation pipelines using cutting-edge AI models (LLMs, VLMs, etc.)
  
  
• Collaborate with Engineering and Ops to enhance our human-in-the-loop pricing systems
  
  
• Improve the feature engineering and model training pipelines that power our production systems
  
  
• Rethink our risk and optimization models using real-world data and domain insight
  
  

We’re a small, nimble team — there’s ample opportunity to work across the entire research and modeling stack.

Compensation

The base pay range for this position is $156,800-$310,000 annually, plus RSUs. Pay within this range varies by work location and may also depend on your qualifications, job-related knowledge, skills, and experience. We also offer a comprehensive package of benefits including unlimited PTO, medical/dental/vision insurance, life insurance, and 401(k) to eligible employees.

#LI-RO

About the Role

What You'll Need

• Experience developing quantitative models to support real-world decision-making under uncertainty
• Strong coding skills in Python, with the ability to move beyond prototyping and implement production-quality scientific code
• Experience with one or more of the following: causal inference, Bayesian modeling, structural modeling, demand forecasting, pricing science, or mathematical optimization
• Comfort working with messy, high-dimensional real-world data and translating ambiguous business problems into rigorous modeling approaches
• Advanced degree (MS or PhD preferred) in statistics, mathematics, economics, operations research, computer science, or another quantitative discipline
• Strong communication and collaboration skills — you’re comfortable working with cross-functional stakeholders and can communicate technical ideas clearly

Nice to Have

What You'll Do

Compensation

About the Role

What You'll Need

• Experience developing quantitative models to support real-world decision-making under uncertainty
• Strong coding skills in Python, with the ability to move beyond prototyping and implement production-quality scientific code
• Experience with one or more of the following: causal inference, Bayesian modeling, structural modeling, demand forecasting, pricing science, or mathematical optimization
• Comfort working with messy, high-dimensional real-world data and translating ambiguous business problems into rigorous modeling approaches
• Advanced degree (MS or PhD preferred) in statistics, mathematics, economics, operations research, computer science, or another quantitative discipline
• Strong communication and collaboration skills — you’re comfortable working with cross-functional stakeholders and can communicate technical ideas clearly

Nice to Have

What You'll Do

Compensation

Why job seekers choose Geotab:

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. 

About The Role

As an Applied Machine Learning Research Scientist at Cerebras, you will play a key role in turning modern machine learning techniques into scalable, high-performance systems. This role sits at the intersection of modeling and systems focused not on publishing new algorithms, but on understanding how they work and making them run effectively at scale. Your work will directly impact how large language models (LLMs) are trained, optimized, and deployed on one of the most advanced AI platforms in the world. 

You will work closely with researchers and senior engineers to implement and improve workflows for LLM pretraining, fine-tuning, and reinforcement learning-based post-training. This includes building training pipelines, debugging complex system behaviors, improving model quality, and iterating on data and evaluation strategies. Your contributions will help translate cutting-edge ML ideas into reliable, production-ready systems that solve real-world problems. 

This role is ideal for candidates who enjoy hands-on engineering, want to build deep intuition for ML systems, and are excited about working on LLMs and reinforcement learning in practice, not just in theory. 

Responsibilities 

• Apply post-training techniques (e.g. RLVR, RLHF, GRPO etc.) techniques to improve model performance.
• Build and maintain evaluation pipelines to measure model performance across tasks and domains.
• Debug issues across the ML stack, including data pipelines, training jobs, model outputs and mixed or lower precision computation.
• Collaborate with researchers to translate ML ideas into efficient, scalable implementation.
• Design, implement, and scale ML pipelines across all stages of LLM development (pretraining, fine-tuning, alignment).
• Work with large datasets, including dataset generation, filtering, and synthetic data approaches.
• Optimize training and inference workflows for performance, efficiency, and reliability.
• Contribute high-quality, maintainable code to shared ML infrastructure. 

Skills & Qualifications    

•  Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
• 0 - 5 years of experience (including internships, research, or industry experience) working with machine learning systems; we are hiring multiple positions for various levels. 
• Strong programming skills in Python.
• Experience with ML frameworks such as PyTorch.
• Solid understanding of machine learning fundamentals.
• Familiarity with deep learning architectures, particularly transformers.
• Ability to read and understand modern ML papers and implement key ideas.

Preferred Skills & Qualifications 

• Experience working with large language models (training, fine-tuning, and evaluation).
• Familiarity with reinforcement learning concepts.
• Experience with distributed training frameworks (e.g., FSDP, Megatron).
• Experience working with large-scale datasets and data pipelines.
• Experience debugging or optimizing ML systems for performance.
  • Contributions to meaningful codebases, projects, or open-source systems 

Are you driven by data, inspired by innovation, and eager to shape the future of insurance?

Join a fast-growing Canadian P&C insurer where you'll play a pivotal role in advancing our Actuarial Services function. We're building on a solid foundation—powered by cutting-edge technology, a robust enterprise data analytics team, and bold investments in AI. With this groundwork in place our talented team is now focused on scaling and refining our capabilities.

We're looking for bright, analytical minds to help bring our strategy to life. If you're passionate about solving complex problems and want to explore Pricing, Underwriting, and Claims, we want to hear from you.

Senior Data Scientist

We're looking for a Senior Data Scientist to join our growing team and build the next generation of predictive analytics solutions. In this role, you won’t just be crunching numbers, you’ll be using machine learning (ML) and artificial intelligence (AI) models to transform raw data into powerful insights that drive our business forward.

This is an opportunity to directly contribute to our core operations, working alongside a supportive team who are invested in your growth. If you have a passion for data and a desire to see your work make a tangible impact, this role is for you.

What you'll do:

• Deliver value through data-driven algorithms and models: You will apply the right mix of ML and AI to solve high-impact business problems. You’ll partner with stakeholders to select and defend the best model architecture and explainability approaches to balance performance, interpretability, and trade-offs.
• Embed ML/AI into core business capabilities: You will build deep expertise in P&C insurance workflows and translate that knowledge into practical ML/AI-powered analyses, decision tools, and visualizations that improve how work gets done.
• Partner with stakeholders to ensure adoption, value, and model integrity: You’ll align with stakeholders on goals and success metrics, then pressure-test solutions against real constraints to ensure they’re feasible and valuable. You will communicate your insights and recommendations with clarity and confidence to both technical and non-technical audiences.
• Invest in Your Future: We're committed to your professional development. You'll engage in project-specific research to continually grow your skills and have the unique opportunity to collaborate with our Claims and Finance departments.

 What You’ll Need to Succeed

• Education: You have a master’s degree in a quantitative or technical discipline
• Experience: You have 3–5 years of experience in an ML/AI development role, with experience deploying ML / AI models into production and associated governance procedures.
• Technical Skills: You have a broad understanding of modern ML architectures, familiarity with cloud and ML platforms. You have strong Python programming skills and experience with various ML libraries.
• Core Competencies: You have excellent analytical, quantitative, and critical thinking skills. You are highly analytical and use your communication and collaboration skills to engage with stakeholders to solve problems.

If you're ready to be a core part of our mission and make a tangible impact from day one, we want to hear from you.

#LI-Hybrid

The expected base salary range for this position is $79,500 - $129,500. Depending on your relevant experience, skills, qualifications, market conditions and business needs, base compensation may vary. You have the potential to earn more through Gore Mutual’s discretionary bonus program which gives you an opportunity to increase your total compensation, provided the business meets its performance targets and you meet your individual goals.

Please note: This range reflects the expected base salary for this role but may not represent the full compensation range for all experience and skill levels. During the recruitment process, we will discuss and consider how your unique qualifications align with the broader range for this position.

Gore Mutual is proud to offer a comprehensive total rewards package which includes extended health and dental benefits, disability insurance, retirement plan matching, paid time off, recognition and perk programs.

About this Role

The Ads Data team is building the next generation of advertising products for the wholesale industry. As a key member of this team, you’ll help drive the ML algorithm strategy and system design behind one of the most critical levers for customer value and company growth—Search Ads. You’ll lead the advancement of real-time systems that decide which ads to show for a query, where to place them, and how to optimize for relevance, marketplace health, and advertiser outcomes. This role mirrors many of the technical expectations of Faire’s organic Search roles (modern NLP/LLMs, query understanding, real-time ranking), while operating in an ads environment with auctions, budgets, and pacing constraints.

You’ll operate at the forefront of algorithms—combining large language models, natural language processing, query understanding, deep learning, and structured behavioral data to deliver highly relevant sponsored results for any given query.

What You'll Do

• Own and evolve the Search Ads relevance stack—spanning query understanding, targeting, candidate generation, multi-stage ranking, and calibration—while meeting stringent latency and reliability goals.
• Design and productionize ML models that improve sponsored-result relevance and personalization, using a blend of unstructured signals (text/images where applicable), LLM-based representations, and structured marketplace features.
• Partner closely with engineering and product to connect relevance improvements to ads marketplace outcomes (e.g., conversion, long-term retailer experience, advertiser ROI), using rigorous offline evaluation and online experiments.
• As an early member of the Ads Data team, help define its roadmap and technical culture, leveraging deep product intuition to shape what ads at Faire should be—not just how they’re built.
• Work in a fast-paced, collaborative environment with team members who’ve shipped ML at top tech companies (e.g. Uber, Airbnb, Meta, Amazon, Pinterest).

Qualifications

• 4+ years of experience building and shipping ML systems in production, with meaningful experience in search, recommendation, or ads ranking/retrieval.
• Hands-on experience with modern deep learning tooling (e.g., PyTorch) and familiarity with vector search / embedding-based retrieval concepts (e.g., Faiss, ScaNN, Pinecone).
• A strong track record of productionizing models that blend LLMs (e.g., BERT / GPT-class) with structured features to drive relevance and personalization.
• Product-focused mindset and a bias toward execution—moving quickly from research to measurable user and business impact.
• Strong communication skills and the ability to work with others in a closely collaborative team environment

Great to Haves

• Highly recommended: Master’s or PhD in Computer Science, Statistics, or related STEM fields
• Ability to quickly implement state of the art algorithms from an academic paper

Salary Range

San Francisco: the pay range for this role is $196,000 to $269,500 per year.

This role will also be eligible for equity and benefits. Actual base pay will be determined based on permissible factors such as transferable skills, work experience, market demands, and primary work location. The base pay range provided is subject to change and may be modified in the future.

About this Role

The Ads Data team is building the next generation of advertising products for the wholesale industry. As a key member of this team, you’ll help drive the ML algorithm strategy and system design behind one of the most critical levers for customer value and company growth—Search Ads. You’ll lead the advancement of real-time systems that decide which ads to show for a query, where to place them, and how to optimize for relevance, marketplace health, and advertiser outcomes. This role mirrors many of the technical expectations of Faire’s organic Search roles (modern NLP/LLMs, query understanding, real-time ranking), while operating in an ads environment with auctions, budgets, and pacing constraints.

You’ll operate at the forefront of algorithms—combining large language models, natural language processing, query understanding, deep learning, and structured behavioral data to deliver highly relevant sponsored results for any given query.

What You'll Do

• Own and evolve the Search Ads relevance stack—spanning query understanding, targeting, candidate generation, multi-stage ranking, and calibration—while meeting stringent latency and reliability goals.
• Design and productionize ML models that improve sponsored-result relevance and personalization, using a blend of unstructured signals (text/images where applicable), LLM-based representations, and structured marketplace features.
• Partner closely with engineering and product to connect relevance improvements to ads marketplace outcomes (e.g., conversion, long-term retailer experience, advertiser ROI), using rigorous offline evaluation and online experiments.
• As an early member of the Ads Data team, help define its roadmap and technical culture, leveraging deep product intuition to shape what ads at Faire should be—not just how they’re built.
• Work in a fast-paced, collaborative environment with team members who’ve shipped ML at top tech companies (e.g. Uber, Airbnb, Meta, Amazon, Pinterest).

Qualifications

• 2+ years of experience building and shipping ML systems in production, with meaningful experience in search, recommendation, or ads ranking/retrieval.
• Hands-on experience with modern deep learning tooling (e.g., PyTorch) and familiarity with vector search / embedding-based retrieval concepts (e.g., Faiss, ScaNN, Pinecone).
• A strong track record of productionizing models that blend LLMs (e.g., BERT / GPT-class) with structured features to drive relevance and personalization.
• Product-focused mindset and a bias toward execution—moving quickly from research to measurable user and business impact.
• Strong communication skills and the ability to work with others in a closely collaborative team environment

Great to Haves

• Highly recommended: Master’s or PhD in Computer Science, Statistics, or related STEM fields
• Ability to quickly implement state of the art algorithms from an academic paper

Salary Range

San Francisco: the pay range for this role is $165,500 to $227,500 per year.

This role will also be eligible for equity and benefits. Actual base pay will be determined based on permissible factors such as transferable skills, work experience, market demands, and primary work location. The base pay range provided is subject to change and may be modified in the future.

About this role

As a Senior Applied AI/ML Scientist on the Search ranking team, you will help shape the technical vision, machine-learning algorithm strategy, and system design behind one of our most important growth levers: Search (the primary tool used by customers on any e-commerce site). You will advance real-time search and recommendation systems that power next-generation shopping experiences.

You’ll work at the frontier of algorithms, combining query understanding, deep learning, transformer-based sequential modeling, graph neural networks, and structured behavioral data to return hyper-relevant, personalized products and brands for every user query.

This is a rare chance to influence the end-to-end personalized discovery experience at Faire within a high-scale, deeply multi-modal environment, while collaborating closely with a talented team of scientists and engineers.

What you'll do

• Build our next-generation Search ranking algorithms by integrating the latest advances in deep learning and machine learning to personalize the retailer discovery journey at Faire
• Leverage LLM to extract multimodal signals (text, visual) to better profile users and their intents. 
• Partner closely with teams across Faire to experiment and improve the ML models for search ranking and beyond.
• Design and productionize natural-language search and discovery systems so that intelligent agents can generate relevant and personalized collections, explain search results, and assist retailers with browsing, filtering, and evaluation.
• Share best practices regarding deep learning model development, agent-workflow evaluation, and MLOps, and help teammates level up through code reviews and technical guidance.

You're a great fit if you have...

• 5+ years of industry experience building large-scale ML models with business impact and shipping ML solutions to production, including 3+ years in search, recommendation, or ads ranking
• A Master’s or PhD in Computer Science, Statistics, or a related STEM field.
• Strong programming skills (Python, Java, or equivalent) and hands-on experience with deep-learning libraries (e.g., PyTorch) and big data technologies (e.g., Spark).
• Deep understanding of machine learning best practices (e.g., training/serving, imbalanced data, A/B testing, feature engineering, and feature/model selection) and algorithms (e.g., user modeling, deep learning, and reinforcement learning) with applications in search, recommendation, and advertising domains.
• A product-focused mindset and a bias toward execution—moving quickly from research papers to prototypes and production.
• Excellent written and verbal communication skills and strong cross-functional influence that raise the technical bar beyond your immediate team.

Bonus points for...

• Contributions to open-source ML libraries or peer-reviewed publications in ML/AI.
• Industry experience developing and productizing LLM-based applications and systems in the search domain.
• Industry experience building search and recommendation systems for e-commerce or two-sided marketplaces.
• Experience using AI tools (e.g., Cursor, Claude Code, Codex) for code development and daily productivity.
• Familiarity with Kotlin

Salary Range

California: the pay range for this role is $192,000 to $264,000 per year.

This role will also be eligible for equity and benefits. Actual base pay will be determined based on permissible factors such as transferable skills, work experience, market demands, and primary work location. The base pay range provided is subject to change and may be modified in the future.