Senior Machine Learning Engineer, Dynamic Pricing Job at Uber (Sunnyvale)

Senior Staff Machine Learning Engineer - Driver Pricing & Marketplace Optimization

We’re seeking an exceptional Senior Staff ML Engineer to lead breakthrough ML in...

Location

United States , Sunnyvale, California; San Francisco, California

Salary:

267000.00 - 297000.00 USD / Year

Uber

Expiration Date

Until further notice

Requirements

PhD in Computer Science, Machine Learning, Operations Research, or related quantitative field OR Master’s degree with 12+ years of industry experience
10+ years of experience building and deploying ML models in large-scale production environments
Expert-level proficiency in modern ML frameworks (TensorFlow, PyTorch, JAX) and distributed computing platforms (Spark, Ray)
Deep expertise across multiple areas including: Deep Learning, Causal Inference, Reinforcement Learning, Multi-objective Optimization, Algorithmic Game Theory, and Large-scale Ads Ranking/Auction Systems
Proven track record of leading complex ML projects from research through production with significant measurable business impact
Strong programming skills in Python, Java, or Go with experience building production ML systems
Experience with feature engineering, model serving, and ML infrastructure at scale (handling millions of predictions per second)
Technical leadership experience including mentoring senior engineers and driving cross-team technical initiatives

Job Responsibility

Lead the design and implementation of advanced ML systems for dynamic pricing algorithms serving millions of drivers across 70+ countries around the world
Architect real-time ML infrastructure handling 1M+ pricing decisions per second with sub-50ms latency requirements
Drive breakthrough research in causal ML, reinforcement learning, algorithmic game theory, and multi-objective optimization for marketplace optimization with strategic agents
Own end-to-end ML model lifecycle from research through production deployment and continuous optimization
Build scalable ML architecture and feature management systems supporting Driver Pricing and broader Marketplace teams
Design experimentation frameworks enabling rapid testing of pricing algorithms using A/B, Switchback, Synthetic Control, and other experimental methodologies
Establish ML engineering best practices, monitoring, and operational excellence across the organization
Create platform abstractions that enable other ML engineers to iterate faster on pricing algorithms
Partner with Product, Operations, and Earner Experience teams to translate complex business requirements into ML solutions
Collaborate with Marketplace Engineering and Science teams to productionize cutting-edge ML research

What we offer

Eligible to participate in Uber's bonus program
May be offered an equity award & other types of comp
Eligible for various benefits

Fulltime

Senior Machine Learning Engineer - Earner Incentive

Uber’s Marketplace is at the core of the business. The Earner Incentive team in ...

Location

United States , Seattle; San Francisco; Sunnyvale

Salary:

202000.00 - 224000.00 USD / Year

Uber

Expiration Date

Until further notice

Requirements

Ph.D., M.S., or Bachelor’s degree in Computer Science, Statistics, Mathematics, Machine Learning, Operations Research, or a related field, or equivalent practical experience with demonstrated impact
5+ years of experience across the end-to-end ML lifecycle, including data analysis, feature engineering, model development, deployment, monitoring, and iteration in large-scale production systems
Proven ability to deliver measurable business impact and strong understanding of MLOps best practices
Strong understanding of a broad range of ML and statistical techniques, including deep learning (e.g., multi-task learning, transformers), tree-based models, and classical approaches
Proficiency in at least one production language (Python, Scala, Java, or Go) and common ML frameworks (e.g., PyTorch, TensorFlow, scikit-learn)
Solid software engineering skills, including system design, writing and reviewing production-quality code, testing, and operating ML systems in production
Strong ownership, learning mindset, collaboration and communication skills
able to work independently and effectively in cross-functional teams

Job Responsibility

Design, develop, productionize, and operate end-to-end ML solutions and data pipelines for large-scale systems that power driver incentives
Develop and apply advanced ML and optimization techniques to design incentive mechanisms for online marketplaces
Build deep domain expertise in incentives, pricing, and marketplace dynamics, and understand how these systems interact with Operations
Help set the team’s technical direction and drive execution in partnership with technical leads
Collaborate closely with engineers, product managers, scientists, and Operations to drive clarity, alignment, and delivery of high-impact solutions
Own projects end-to-end, from ideation and design through production rollout and iteration, and drive measurable business impact across teams

What we offer

Eligible to participate in Uber's bonus program
May be offered an equity award & other types of comp
All full-time employees are eligible to participate in a 401(k) plan
Eligible for various benefits

Fulltime

Senior Software Engineer - Dynamic Pricing

The mission of the Trip Value team is to improve the rider & driver experience b...

Location

United States , New York, New York; San Francisco, California; Sunnyvale, California

Salary:

202000.00 - 224000.00 USD / Year

Uber

Expiration Date

Until further notice

Requirements

Bachelor's degree or equivalent in Computer Science, Engineering, Mathematics or related field
5+ years of full-time Software Engineering work experience
Proficient in a language such as Java/Go/Python
Experience building scalable distributed systems
Familiarity with in-memory datastores (e.g. Redis, Memcached)
Masters/PhD in relevant fields (CS, EE, Math, Stats, etc.) with a focus on Machine Learning
3+ years of experience in an ML role with an emphasis on data and experiment driven model development
Expertise in deep learning and optimization algorithms
Experience with ML frameworks such as PyTorch and TensorFlow
Experience building and productionizing innovative end-to-end Machine Learning systems

Job Responsibility

You will work with a mixed team of Engineers, Operations Researchers, and Economists to build large-scale optimization systems based on real-time marketplace conditions for Uber's rides products globally

What we offer

Eligibility to participate in Uber's bonus program
May be offered an equity award & other types of comp
Eligibility to participate in a 401(k) plan
Eligibility for various benefits

Fulltime

Data Science Team Leader

As the Senior Team Lead for Data Science - Logistics Estimations, you will be th...

Location

Germany; United Kingdom; Netherlands , Berlin; London; Amsterdam

Salary:

Not provided

Just Eat Takeaway.com

Expiration Date

Until further notice

Requirements

Proven, extensive experience in leadership and people management, with a demonstrated ability to mentor, guide, and develop Data Scientists
Prior hands-on experience developing, deploying, and maintaining machine learning models in a corporate environment
Advanced conceptual proficiency in data science and machine learning methodologies, ideally with experience in logistics, geospatial analysis, and ETA prediction or routing problems
Demonstrated experience in root-cause analysis of complex production model performance issues and the ability to translate those findings into effective business and technical solutions
Strong understanding of the model lifecycle and best practices, including testing, code reviews, and monitoring
Exceptional communication and stakeholder management skills, with the ability to influence technical peers and non-technical business leaders

Job Responsibility

Team Leadership: Mentor and manage a high-performing Data Science team, fostering a culture of speed, rigor, and courier-centric problem-solving
Strategy & Roadmap: Own the data science strategy for real-time courier pay systems, including dynamic earnings, surge pricing, and incentive programs
KPI Ownership: Drive critical business outcomes by taking ownership of key courier supply metrics like availability, acceptance rates, and earnings competitiveness
Root Cause Analysis & Communication: Diagnose structural and behavioral supply issues and translate complex economic models into actionable narratives for cross-functional stakeholders
Real-Time Architecture: Design the conceptual framework for real-time incentive engines, balancing advanced model sophistication with strict latency and reliability constraints
Dynamic Pricing: Oversee the development of predictive models that address local supply-demand imbalances and optimize real-time boost levels
Fairness & Technical Standards: Act as the senior technical guide to ensure pay models are rigorous, auditable, mathematically consistent, and free from unintended bias
MLE Collaboration: Partner closely with Machine Learning Engineers to ensure smooth, robust deployment and scaling of production-ready models
Causal Experimentation: Lead the design and execution of complex marketplace experiments to accurately measure the real-world impact of pay and incentive changes
Behavioral Modeling & ROI: Direct the modeling of courier behavior (elasticity, churn, engagement) and build frameworks to maximize the ROI of incentive spend using large-scale geospatial data

Fulltime

Principal Product Manager, Rides Matching

We are looking for a Principal Product Manager to join the Rides team at Bolt. I...

Location

Estonia; Germany , Tallinn; Berlin

Salary:

Not provided

Bolt

Expiration Date

Until further notice

Requirements

You have experience shipping machine learning models into production systems that serve real-time allocations at scale, including ownership of the full lifecycle from feature engineering and training through shadow deployment, monitoring, and iteration
You have worked on allocation, matching, dispatch, or equivalent real-time systems in a two-sided marketplace, logistics platform, or high-throughput environment, with a strong grasp of supply-demand dynamics and global versus local optimisation trade-offs
You have navigated the complexity of maintaining a live production system while simultaneously building its replacement, with a track record of keeping current performance stable through a migration
You have coordinated cross-functional product pods and have experience working across organisational boundaries, including negotiating interface contracts and mutual accountability with adjacent teams such as pricing or economics
You are able to move fluently between detailed statistical evaluation and clear stakeholder communication, and you produce high-quality written deliverables including strategy documents, technical specifications, and experiment reviews
You have direct exposure to reinforcement learning in production, or have worked with teams that deployed RL systems, with a solid grasp of reward design, exploration-exploitation trade-offs, and the gap between simulation and live environments
At Bolt, using AI daily is a baseline expectation for everyone

Job Responsibility

Define the product strategy and roadmap for the dispatching engine, sequencing foundational ML/RL investments alongside near-term improvements to queue ranking, dispatch strategy, and retry governance
Coordinate the productionisation of machine learning and reinforcement learning models, from offline training through shadow mode, A/B testing, incremental rollout, and live monitoring across multiple markets
Own and improve the performance of the existing matching stack while the new engine is being built, maintaining stability and delivering incremental efficiency gains
Define and maintain the signal contract between matching and pricing, ensuring matching delivers reliable, low-latency completion probability and supply density signals
Design experiments, evaluate results, and translate complex algorithmic trade-offs into clear recommendations for senior stakeholders and cross-functional peers
Set priorities and resolve trade-offs within a cross-functional pod spanning product, engineering, data science, and specialist roles, acting as the accountable owner for matching KPIs

What we offer

Accelerate your professional growth with unique career opportunities
Enjoy a rewarding salary and stock options, knowing that as Bolt succeeds, so do you
Take care of your physical and mental health with our wellness perks
Celebrate 5 years at Bolt with a 1-month paid sabbatical to recharge
Connect with colleagues at annual company events and smaller team gatherings
Balance flexibility and in-person collaboration with our hybrid model, including at least 12 monthly in-office days

Fulltime

Principal Product Manager, Rides Matching

We are looking for a Principal Product Manager to join the Rides team at Bolt. I...

Location

Estonia; Germany , Tallinn; Berlin

Salary:

Not provided

Bolt

Expiration Date

Until further notice

Requirements

You have experience shipping machine learning models into production systems that serve real-time allocations at scale, including ownership of the full lifecycle from feature engineering and training through shadow deployment, monitoring, and iteration
You have worked on allocation, matching, dispatch, or equivalent real-time systems in a two-sided marketplace, logistics platform, or high-throughput environment, with a strong grasp of supply-demand dynamics and global versus local optimisation trade-offs
You have navigated the complexity of maintaining a live production system while simultaneously building its replacement, with a track record of keeping current performance stable through a migration
You have coordinated cross-functional product pods and have experience working across organisational boundaries, including negotiating interface contracts and mutual accountability with adjacent teams such as pricing or economics
You are able to move fluently between detailed statistical evaluation and clear stakeholder communication, and you produce high-quality written deliverables including strategy documents, technical specifications, and experiment reviews
You have direct exposure to reinforcement learning in production, or have worked with teams that deployed RL systems, with a solid grasp of reward design, exploration-exploitation trade-offs, and the gap between simulation and live environments
At Bolt, using AI daily is a baseline expectation for everyone

Job Responsibility

Define the product strategy and roadmap for the dispatching engine, sequencing foundational ML/RL investments alongside near-term improvements to queue ranking, dispatch strategy, and retry governance
Coordinate the productionisation of machine learning and reinforcement learning models, from offline training through shadow mode, A/B testing, incremental rollout, and live monitoring across multiple markets
Own and improve the performance of the existing matching stack while the new engine is being built, maintaining stability and delivering incremental efficiency gains
Define and maintain the signal contract between matching and pricing, ensuring matching delivers reliable, low-latency completion probability and supply density signals
Design experiments, evaluate results, and translate complex algorithmic trade-offs into clear recommendations for senior stakeholders and cross-functional peers
Set priorities and resolve trade-offs within a cross-functional pod spanning product, engineering, data science, and specialist roles, acting as the accountable owner for matching KPIs

What we offer

Accelerate your professional growth with unique career opportunities
Enjoy a rewarding salary and stock options
Take care of your physical and mental health with our wellness perks
1-month paid sabbatical after 5 years
Annual company events and smaller team gatherings
Hybrid model with at least 12 monthly in-office days

Fulltime

Engineering Manager, Listings Products

Airbnb was born in 2007 when two hosts welcomed three guests to their San Franci...

Location

United States

Salary:

204000.00 - 255000.00 USD / Year

Airbnb

Expiration Date

Until further notice

Requirements

9+ years of industry experience, with a minimum of 3-5 years in engineering management
Track record of strong partnership with design and product leadership, through proactive collaboration, building prototypes, and leadership demos
Expertise in setting 1-2 year technical strategies and roadmaps, aligning vision with diverse executive and technical stakeholders
Demonstrated experience leading high-performing, healthy, inclusive and collaborative teams quickly in dynamic, fast-paced domains
Exceptional people management and mentorship skills, with a history of recruiting, developing and retaining top engineering talent

Job Responsibility

Define and execute strategy to dramatically improve the Host Listing Management experience through AI and data capabilities
Set priorities, balance speed and quality, and ensure the engineering team executes against an ambitious roadmap
Partner with Product, Design, and ML/Data teams to take high-impact initiatives from concept to production
Drive the technical foundation and ensure that we’re maintainable and extensible software
Lead and mentor a diverse team of ~8+ engineers and technical leads across mobile native, web frontend, and backend services
Partner with senior leadership in Engineering, Product, and Design and across our Business to align stakeholders, define multi-year roadmaps, set and execute on iterative milestones
Collaborate closely with key engineering teams, including Listings Foundation, Calendar, Pricing, Guest Experience, Trust, Infrastructure, and Customer Service Platform
Coaching and developing team members, helping them grow their careers, technical expertise, and collaboration skills

What we offer

bonus
equity
Employee Travel Credits

Fulltime

Senior Scientist, Direct

We’re hiring a Senior Scientist for the Uber Direct team—one of Uber’s fastest-g...

Location

United States; Canada , New York; Seattle; San Francisco; Toronto

Salary:

173000.00 - 211000.00 USD; CAD / Year

Uber

Expiration Date

Until further notice

Requirements

Ph.D., M.S., or Bachelor's degree in Economics, Operations Research, or a related quantitative field (e.g., Statistics, Applied Mathematics, Computer Science with a strong modeling focus)
Strong foundation in marketplace modeling and dynamics, including experimental design (e.g., A/B testing), causal inference, and optimization techniques
Proficiency in SQL and experience using Python or R for data analysis, modeling, and prototyping
Demonstrated ability to extract insights from complex datasets, distill them into actionable strategies, and influence product and business decisions
Excellent written and verbal communication skills, with the ability to clearly explain technical concepts to cross-functional stakeholders and drive alignment across teams

Job Responsibility

Leverage advanced analytical and quantitative techniques—including machine learning, statistical modeling, causal inference, funnel analysis, and deep-dive analytics—to build a best-in-class delivery experience for Uber’s Direct business
Translate complex analyses into clear, actionable insights and effectively communicate findings to executives, business leaders, and cross-functional stakeholders to shape product and business strategy
Collaborate closely with Product, Engineering, and Operations teams to define and drive a roadmap of high-impact initiatives, ensuring that marketplace design, pricing, and fulfillment strategies are informed by rigorous analysis and competitive intelligence
Provide technical mentorship and thought leadership, raising the bar for scientific rigor, championing best practices in statistical and machine learning methodologies, and fostering a strong culture of data-driven decision-making

What we offer

Eligible to participate in Uber's bonus program
May be offered an equity award & other types of comp
Eligible to participate in a 401(k) plan
Various benefits

Fulltime

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Senior Machine Learning Engineer, Dynamic Pricing

Job Description

Job Responsibility

Requirements

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