Riot’s Data Engineers harness petabytes of data and state-of-the-art processing technologies to build products that elevate the player experience at massive scale. Turning this data into meaningful insights is a complex challenge, and our engineers meet it by staying deeply player-focused and collaborating across diverse teams to improve the lives of millions of players worldwide.

As a Principal Data Engineer supporting Riot’s Publishing Platform team, you will design, build, and maintain scalable data pipelines and models that power critical data products, including centralized player data models, and publishing activity data systems. These systems support understanding of player onboarding funnels, engagement patterns, support efficiency, and content effectiveness. You will collaborate with product managers, analysts, and engineers to ensure our data infrastructure is reliable, performant, and directly tied to delivering better player experiences.

Responsibilities:

• Design, build, and optimize scalable ETL pipelines for structured and semi-structured data supporting Insights use cases, growth metrics, and other publishing/marketing focused data sets.
• Design and implement data models using industry best practices that capture a complete ecosystem view of in- and out-of-game experiences, while ensuring accuracy, scalability, and long-term usability.
• Architect and implement robust, maintainable, and high-performance data solutions.
• Automate workflows to reduce manual intervention and enhance data processing efficiency, including automation for content, growth, and pubsports areas of coverage.
• Mentor data engineers across all levels, setting best practices and fostering technical growth.
• Optimize query performance and resolve pipeline bottlenecks to improve data accessibility.
• Evaluate and adopt new tools, frameworks, and methodologies to advance data engineering capabilities.
• Support cost optimization by ensuring scalable and efficient data solutions.
• Ensure data quality, governance, and compliance with regulatory standards (e.g., GDPR, CCPA).
• Contribute to Riot’s Data Engineering discipline shaping infrastructure, craft standards, tooling, and organizational best practices

Required Qualifications:

• Bachelor's or Master’s degree in Computer Science, Information Systems, Engineering, or a related field.
• 8+ years experience in tech-focused Publishing or Marketing fields.
• 8+ years experience in data engineering or a related field.
• Strong Expertise in big-data technologies, including Python, GoLang, Spark, Scala, SQL, and tools like Airflow and dbt.
• Proficiency in cloud infrastructure (AWS or GCP) and Databricks.
• Expertise in designing efficient and scalable data models with large data sets across multiple teams and in collaboration with insights or data stakeholders.
• Demonstrated ability to work cross-functionally with engineering, analytics, and product teams.
• Proven experience mentoring and guiding other engineers.

For this role, you'll find success through craft expertise, a collaborative spirit, and decision-making that prioritizes your fellow Rioters, who are the customers of your work. Being a dedicated fan of games is not necessary for this position!

Our Perks:

Riot focuses on work/life balance, shown by our open paid time off policy and other perks such as flexible work schedules. We offer medical, dental, and life insurance, parental leave for you, your spouse/domestic partner, and children, and a 401k with company match. Check out our benefits pages for more information.

At Riot Games, we put players first. That mission drives every decision in our quest to create games and experiences that make it better to be a player. Whether you’re working directly on a new player-facing experience or you’re supporting the company as a whole, everyone at Riot is part of our mission. And just like in our games, we’re better when we work together. Our goal is to create collaborative teams where you are empowered to bring your unique perspective everyday. If that sounds like the kind of place you want to work, we’re looking forward to your application.

It’s our policy to provide equal employment opportunity for all applicants and members of Riot Games, Inc. Riot Games makes reasonable accommodations for handicapped and disabled Rioters and does not unlawfully discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, handicap, veteran status, marital status, criminal history, or any other category protected by applicable federal and state law. We consider for employment all qualified applicants, including those with criminal histories, in a manner consistent with applicable federal, state and local law, including the California Fair Chance Act, the City of Los Angeles Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, the San Francisco Fair Chance Ordinance, and the Washington Fair Chance Act.

Per the Los Angeles County Fair Chance Ordinance, the following core duties may create a basis for disqualifying candidates with relevant criminal histories:

• Safeguarding confidential and sensitive Company data
• Communication with others, including Rioters and third parties such as vendors, and/or players, including minors
• Accessing Company assets, secure digital systems, and networks
• Ensuring a safe interactive environment for players and other Rioters

These duties are directly related to essential operations, safety, trust, and compliance obligations within our organization. Please note that job duties may evolve based on business needs and additional responsibilities may be assigned as necessary to maintain operational efficiency and security. 

The Data Engineering team builds tools and systems that make Gusto's data consistent, user-friendly, and helpful. This helps our teams make decisions using data and provide intelligent, customized experiences to our customers.

We're looking for a Senior Data Engineer who can take loosely defined problems and drive them end-to-end—from framing the problem and aligning stakeholders to designing, building, and delivering durable data solutions. You’ll partner closely with analytics, product, and engineering teams to deliver data solutions that drive real business and customer impact.

Preferred Qualifications

• 8-10+ years of industry experience in data engineering building scalable data pipelines and data products
• Strong proficiency in SQL and at least one programming language (e.g., Python, Scala, or Java)
• Proven experience building and maintaining robust data pipelines and ETL workflows, with hands-on dbt experience for reliable, testable, and maintainable data transformations.
• Hands-on experience ingesting data from diverse sources, including APIs, databases, SaaS applications, and event streams.
• Strong foundation in data modeling, schema design, and data quality best practices, with functional experience working on cloud platforms like Snowflake, Redshift, BigQuery, or Databricks.
• Experience implementing CI/CD pipelines, automated testing, and data observability to ensure reliability and trust in data systems
• Familiarity with monitoring, alerting, and incident response for production-grade data pipelines
• Proven ability to optimize performance and cost across data workflows and storage systems
• Functional understanding of how to leverage AI and automation in data engineering — building self-service tools, intelligent pipelines, and agents that automate repetitive tasks
• Exemplar problem-solving skills and ability to work collaboratively in cross-functional teams.
• Strong communication and collaboration skills, with a focus on clarity, empathy, and shared ownership

Compensation Details

Our cash compensation amount for this role is targeted at $155,000-$185,000/yr in Denver, $170,000-$200,000/yr in Los Angeles, and $190,000-$220,000/yr for San Francisco, Seattle, and New York. Final offer amounts are determined by multiple factors including candidate experience and expertise and may vary from the amounts listed above.

Who we are

The real world is the next frontier, and at Metropolis, we are creating the artificial intelligence to make it responsive. We are pioneering the Recognition Economy — a future where mundane repetition disappears and being known unlocks access, comfort, and belonging everywhere you go. From transforming parking into a seamless drive-in, drive-out experience for millions of Members to expanding our intelligence layer across retail and hospitality, we are building a world that feels instinctive and magical. The future isn’t coming; it’s here, and we need builders, innovators, and problem solvers to help us create it.

Who you are

Metropolis is seeking a Senior AI Engineer to join our Applied AI organization, a team purpose-built to rebuild how the company operates from an AI-first perspective. You will be the builder at the heart of this transformation, designing and shipping AI-powered tools and automation pipelines that replace manual, repetitive work across finance, operations, revenue, and beyond. This is a hands-on engineering role with enormous scope: you will own systems end-to-end, from the LLM prompt layer through to production deployment, working side-by-side with Process Analysts who understand the business deeply. If you want to see your work directly change how a company functions — not someday, but now — this is the role.

What you'll do

• Design, build, and ship AI-powered automation tools and internal applications that transform manual business processes into AI-first workflows
• Architect and maintain LLM-based systems, including prompt pipelines, agentic workflows, tool-calling integrations, and retrieval-augmented generation (RAG) setups
• Build and maintain data pipelines that connect source systems (Snowflake, internal APIs, SaaS tools) to AI workflows, ensuring data quality and reliability
• Partner with Process Analysts to understand how business functions work today, translate requirements into engineering specifications, and iterate based on real user feedback
• Own production reliability for the systems you build — monitoring, alerting, and iterating on AI outputs to maintain quality over time
• Evaluate and integrate emerging AI tooling (models, frameworks, APIs) to ensure Metropolis is always leveraging the best available capabilities
• Contribute to internal standards for AI development: prompt management, evaluation frameworks, model selection, and system architecture

What we're looking for

• 6+ years of software engineering experience, with 2+ years of hands-on experience designing, building, and deploying LLM-based or AI-powered applications in production
• Strong Python skills — you write clean, maintainable code and are comfortable building APIs, data pipelines, and backend services
• Practical experience with LLM APIs (OpenAI, Anthropic, or similar), prompt engineering, and agentic patterns (function calling, multi-step reasoning, tool use)
• Familiarity with data engineering fundamentals: SQL, data transformation, working with cloud data warehouses (Snowflake preferred)
• Experience with workflow orchestration tools (e.g., Airflow, Prefect, or similar) and cloud infrastructure (AWS preferred)
• A strong instinct for product quality — you care about whether the tools you build are actually useful, not just technically functional
• Ability to work autonomously in a fast-moving environment, manage competing priorities, and ship iteratively rather than waiting for perfection

While not required, these are a plus:

• Experience with vector databases, embeddings, or semantic search is a plus

Our Stack

• Languages + Frameworks: TypeScript, React, Scala (principally), Java (limited)
• Datastores: MySQL, PostgreSQL, Snowflake
• Cloud: AWS
• Version control: Git & GitHub
• AI Tooling: Copilot on GitHub and Claude Code
• Observability: Datadog

4 Days in Office: Metropolis values in-person collaboration to drive innovation, strengthen culture, and enhance the Member experience. Our corporate team members hold to our office-first model, which requires employees to be on-site at least four days a week, fostering organic interactions that spark creativity and connection

When you join Metropolis, you'll join a team of world-class product leaders and engineers, building an ecosystem of technologies at the intersection of parking, mobility, and real estate. Our goal is to build an inclusive culture where everyone has a voice and the best idea wins. You will play a key role in building and maintaining this culture as our organization grows. The anticipated base salary for this position is $170,000.00 USD to $200,000.00 USD annually. The actual base salary offered is determined by a number of variables, including, as appropriate, the applicant's qualifications for the position, years of relevant experience, distinctive skills, level of education attained, certifications or other professional licenses held, and the location of residence and/or place of employment. Base salary is one component of Metropolis' total compensation package, which may also include access to or eligibility for healthcare benefits, a 401(k) plan, short-term and long-term disability coverage, basic life insurance, a lucrative stock option plan, bonus plans, and more. #LI-CM1 #LI-Onsite

About this position:

We’re looking for a Machine Learning Infrastructure Engineer to join our growing Data & Platform team and build the foundation that powers our AI and machine learning capabilities across Later’s product portfolio. As our first dedicated ML Infrastructure Engineer, you will own the systems that support model experimentation, training, deployment, and monitoring at scale.

This role is critical to accelerating our data science initiatives and enabling future AI innovation. You’ll design and operate reliable, secure, and scalable ML infrastructure that empowers data scientists and engineers to ship high-impact models with confidence. If you’re excited about building robust ML systems in a fast-moving environment—and want to define the standard for ML Ops at Later—this is your opportunity.

What you'll be doing:

Strategy

• Define and own the long-term ML infrastructure roadmap, ensuring it supports both current experimentation needs and future AI initiatives.
• Establish best practices for model lifecycle management, deployment standards, monitoring, and governance. 
• Identify infrastructure gaps and proactively design scalable solutions to enable high-velocity ML development.
• Contribute to cross-functional technical planning, ensuring ML systems align with product and platform strategy.

Technical/ Execution

• Design, build, and maintain production-grade model deployment and inference systems using CI/CD pipelines, containerized services (Docker), and API frameworks (e.g., Flask).
• Automate end-to-end ML lifecycle workflows including training pipelines, model validation, registry management, deployment, and rollback strategies.
• Implement robust monitoring systems for model performance, latency, drift detection, and infrastructure health using tools such as CloudWatch, Prometheus, and Grafana.
• Operate across AWS and GCP environments to manage training and inference workloads, including GPU-based infrastructure and BigQuery datasets.
• Develop and maintain infrastructure-as-code (Terraform, CloudFormation) to ensure scalable, repeatable, and secure cloud environments.
• Implement and optimize CI/CD workflows (e.g., GitHub Actions, GitLab CI, Bitbucket Pipelines) for ML and infrastructure automation.

Team / Collaboration

• Partner closely with Data Scientists, Analysts, Platform Engineers, and Product Engineers to support end-to-end ML workflows.
• Translate data science experimentation needs into production-ready infrastructure solutions.
• Serve as the technical bridge between ML experimentation and productized deployment.
• Share knowledge and best practices to elevate ML maturity across teams.

Research/Best Practices

• Stay current on emerging ML Ops practices, tools, and frameworks to continuously improve system reliability and efficiency.
• Evaluate and implement model-serving frameworks (e.g., TorchServe, Seldon, TensorRT) where appropriate.
• Contribute to governance, reproducibility, and auditability standards for ML systems.
• Experiment with new tooling and workflows to improve reproducibility, performance, and developer velocity.

What success looks like:

• ML models move from experimentation to production quickly and reliably, with minimal manual intervention.
• CI/CD pipelines enable safe, repeatable deployments with clear rollback strategies.
• Model performance, drift, and infrastructure health are proactively monitored and observable.
• Infrastructure supports scalable GPU training and real-time inference without bottlenecks.
• Data scientists report improved velocity, reproducibility, and confidence in deploying models.
• ML systems are secure, compliant, and aligned with evolving product and AI strategy.

What you bring:

• 4+ years of experience in ML Ops, ML infrastructure, backend engineering, or related roles supporting production ML systems.
• Experience working in cloud-native environments (AWS and/or GCP) with hands-on deployment of ML workloads.
• Proven track record designing and implementing CI/CD pipelines for ML systems.
• Strong experience with Amazon SageMaker, Docker, Flask-based APIs, and infrastructure automation tools.
• Hands-on experience with ML lifecycle tooling such as MLflow, SageMaker Studio, or Weights & Biases.
• Experience managing container orchestration platforms (Kubernetes, EKS, or GKE).
• Strong programming experience in Python (additional experience in Go, Java, or Scala is a plus).
• Experience working with infrastructure-as-code tools such as Terraform or CloudFormation.
• Familiarity with observability tools such as CloudWatch, Prometheus, Grafana, Datadog, or centralized logging platforms.
• Experience managing GPU-based workloads and scaling training/inference systems.
• Familiarity with data infrastructure tools such as BigQuery and cloud-native data pipelines.
• Bonus: Experience supporting LLMs or generative AI pipelines, distributed training systems, feature stores (e.g., Feast), real-time inference systems, or ML governance frameworks.
• A mindset focused on automation, reliability, performance, and continuous improvement in fast-scaling environments.

How you work: 

• Driven by Impact: You deliver results that matter—prioritizing high-value work, meeting deadlines, and adapting quickly while keeping outcomes clear.
• Strategic & Customer-Centric: You anticipate risks and opportunities, connect decisions to long-term growth, and build trust through proactive insights.
• Curious & Growth-Oriented: You seek knowledge, ask sharp questions, and apply learnings fast—challenging the status quo with a mindset of improvement.
• Collaborative & Resilient: You thrive in change by staying resourceful, solution-focused, and positive—removing roadblocks, sharing insights, and keeping morale high.
• Accountable & Honest: You own your work, hold yourself and others to a high bar, and use transparent feedback to drive growth.
• Emotionally Intelligent: You build trust through empathy and collaboration, foster inclusion, and inspire others with grit, optimism, and integrity.

Our approach to compensation:

We take a market-based & data-driven approach to compensation. We leverage data from trusted third-party compensation sources to help us understand the market value of a role based on function, level, geographic location, and scope. We evaluate compensation bi-annually, including performance and market-related factors.

Our salaries are benchmarked against market Total Cash Compensation for the geographic location of our job posting. Compensation for some roles is structured as On Target Earnings (OTE = base + commission/variable) while for others it is structured as Salary only.

To comply with local legislation and ensure transparency, we share salary ranges on all job postings. Skills, experience and other factors help determine the final salary we offer which may vary from the original range posted. 

Additionally, all permanent team members are eligible to participate in various benefits plans as part of their overall compensation package.

Salary Range: 

$ 145,000 -165,000 

#LI-remote

About the Role:

As a Software Engineer on the ML Infrastructure team, you will collaborate closely with the Machine Learning and Product teams to build world-class machine learning inference platforms. These platforms power essential services like personalized recommendations, search, and content understanding across Tubi.

A core responsibility of this team is developing and maintaining low-latency ML model serving systems that support Deep Learning, LLM, and Search models. This involves building self-service infrastructure and critical components such as the inference engine, feature store, vector store, and experimentation engine.

You will improve the way we deploy and operate our services and even contribute to open-source projects. This role grants the architectural freedom to explore new frameworks, lead critical cross-functional projects, and transform the capabilities of our ML and Product teams.

We currently have multiple openings;

• Staff Software Engineer
• Principal Software Engineer
  • Additional Details: As a Principal Engineer on the ML Infrastructure team, you will be a technical leader and visionary, driving the evolution of our machine learning platform. You will tackle the most complex and impactful technical challenges, shaping the architecture and technology choices that enable our ML capabilities to scale and deliver exceptional user experiences. You will be a key influencer, bridging the gap between engineering and product, and a mentor to senior engineers, fostering a culture of technical excellence and continuous improvement. Your work will be used by millions of users.

Responsibilities:

• Design and build scalable, high throughput, and low latency distributed systems using Scala
• Build reusable components and services that serve various ML applications like Personalization, Search, Ads and Exploration
• Partner closely with ML engineers to understand their challenges and limitations and develop scalable solutions to address them. Proactively recommend solutions to keep our ML Inference stack state of the art.
• Take a data driven approach to identifying & optimizing latency, cost, and efficiency of our infra. Lead large scale cross functional refactorings if necessary
• Mentor other engineers on the team on system design, effective incident management, interviewing, leveraging LLMs for work, etc.
• Collaborate with ML, Product, and cross functional engineering teams to define the long term vision and architecture for ML Infrastructure at Tubi.  

Your Background:

• Experience designing and building scalable, distributed systems in any modern backend language (e.g., Scala, Java, Python, Go, C++); experience with Scala or JVM based language is a plus.
• Strong experience with AWS or an equivalent cloud platform
• Experience building online microservices at scale with low latency serving
• Experience with both SQL (e.g. Postgres) and NoSQL databases (e.g. Cassandra), message brokers (e.g. Kafka), and caches (e.g. Redis)
• Experience with containerization technologies, such as Docker or Kubernetes
• Led the response and resolution efforts for multiple major, large-scale incidents

Bonus:

• Familiarity with the machine learning infrastructure like inference engines (e.g. torschserve, triton, vLLM), vector stores (e.g. LanceDB, FAISS), feature stores (e.g. Feast), ElastiCache, model training orchestration, etc.
• Understanding of ML model training pipelines and model internals. Experience with Recommender Systems, Search, Autocomplete and Ads ML is a plus
• Previous experience with Akka, Erlang, Elixir or Go
• Proficient in data-driven analysis of complex A/B testing results

About Tubi:

Tubi is a free streaming service that entertains over 100 million monthly active users. Tubi offers the world's largest collection of Hollywood movies and TV shows, thousands of creator-led stories and hundreds of Tubi Originals made for the most passionate fans. Headquartered in San Francisco and founded in 2014, Tubi is part of Tubi Media Group, a division of Fox Corporation.

#LI-Hybrid

Who we are

Metropolis is an artificial intelligence company that uses computer vision technology to enable frictionless, checkout-free experiences in the real world. Today, we are reimagining parking to enable millions of consumers to just "drive in and drive out." We envision a future where people transact in the real world with a speed, ease, and convenience that is unparalleled, even online. Tomorrow, we will power checkout-free experiences anywhere you go to make the everyday experiences of living, working, and playing remarkable - giving us back our most valuable asset, time.

Who you are

Metropolis is seeking a Staff Software Engineer to join our Revenue Platform team. In this role, you will own the technical direction for our billing, payments, and invoicing infrastructure, charting the course for a system that already processes tens of millions in monthly transactions. You will balance immediate business needs with long-term architectural improvements, identifying high-impact enhancements and designing practical migration strategies to support our rapid growth.

As a technical leader, you will partner closely with engineering, finance, and operations teams to solve complex challenges involving pricing rules, subscription billing, and enterprise invoicing. You are a systems thinker who enjoys understanding how things work and building the roadmaps that improve a platform while it runs. Your work will directly shape how Metropolis monetizes its platform and expands into new verticals beyond parking, ensuring our financial systems remain resilient, compliant, and remarkably efficient.

What you’ll do

• Own the technical architecture and evolution of Metropolis's billing, payments, and invoicing systems, establishing standards for financial accuracy, transaction integrity, and compliance that ensure every dollar is correctly captured and accounted for
• Design and implement resilient payment processing with support for multiple payment gateways (Stripe,  etc.), intelligent routing between processors, retry strategies for failed transactions, and graceful handling of partial failures to maximize payment success rates
• Build comprehensive monitoring and reporting for revenue operations, including payment success rates, billing accuracy metrics, reconciliation dashboards, failed transaction alerts, and audit trails that provide visibility from customer transactions to accounting close
• Partner with finance and operations teams on payment failures, billing disputes, refund workflows, and reconciliation issues – building tools and automation that reduce manual intervention and improve mean time to resolution for customer-impacting revenue issues
• Drive adoption of revenue system best practices across services, including idempotent payment processing, distributed transaction handling, compensation workflows for failures, audit logging, and testing strategies that ensure financial correctness
• Own integrations with external systems, including payment gateways, ERP, data analytics, etc., ensuring reliable data flow and maintaining compliance requirements across the revenue stack

What we’re looking for

• 8+ years of hands-on engineering experience with a focus on building revenue systems like payment platforms
• Strong systems thinking for financial correctness with proven ability to design distributed revenue systems that handle edge cases gracefully: partial failures, duplicate requests, timing issues, currency conversion, tax calculation, and maintaining transaction integrity across service boundaries
• Database and financial data expertise, including transaction isolation, audit logging, point-in-time recovery, handling financial data migrations, and experience with systems that require both high availability and absolute correctness
• Payment gateway and integration experience with production knowledge of Stripe, PayPal, or similar processors; tax calculation services; accounting system integrations; and the operational reality of depending on external financial services, including compliance requirements like PCI-DSS
• Excellent technical communication with the ability to influence technical decisions across teams (particularly finance, accounting, and data teams), document complex systems, conduct post-mortems, and establish reliability standards organization-wide
• Experience with sophisticated usage of rapidly developing AI-assisted development skills in real-world codebases, including fluent use of Claude Code/GPT Codex/Windsurf or similar tools in multi-agent mode, spec-driven development (SDD),  MCP/skills optimization, context/prompt engineering
• Local to the Seattle area

While not required, these are a plus

• BS or MS in Computer Science or a relevant engineering discipline
• Expert-level revenue systems engineering with hands-on experience building billing platforms, payment processing pipelines, reconciliation systems, and handling challenges like idempotent transactions, failed payment retries, proration logic, multi-currency support, and revenue recognition – you've seen these problems before and know the patterns that work
• Expert revenue systems engineering with hands-on experience building billing platforms, payment processing, reconciliation, and managing complex challenges like idempotent transactions, payment retries, proration, multi-currency support, and revenue recognition.
• Financial systems expertise with deep experience implementing audit trails, reconciliation workflows, revenue reporting, and compliance controls at scale – you understand what it takes to maintain penny-perfect accuracy
• Java expertise with a deep understanding of JVM performance, concurrency, and operational characteristics. Scala experience is a big plus
• Experience with AI-powered development tools such as Claude Code, GitHub Copilot, or similar agentic coding tools for enhanced productivity

  Our Stack

• Languages + Frameworks: TypeScript, React, Scala (principally), Java (limited)
• Datastores: MySQL, PostgreSQL, Snowflake
• Cloud: AWS
• Version control: Git & GitHub
• AI Tooling: Copilot on GitHub and Claude Code
• Observability: Datadog

4 Days in Office: Metropolis values in-person collaboration to drive innovation, strengthen culture, and enhance the Member experience. Our corporate team members hold to our office-first model, which requires employees to be on-site at least four days a week, fostering organic interactions that spark creativity and connection.

When you join Metropolis, you'll join a team of world-class product leaders and engineers, building an ecosystem of technologies at the intersection of parking, mobility, and real estate. Our goal is to build an inclusive culture where everyone has a voice and the best idea wins. You will play a key role in building and maintaining this culture as our organization grows. The anticipated base salary for this position is $220,000 USD to $250,000 USD annually. The actual base pay offered is determined by several variables, including, as appropriate, the applicant's qualifications for the position, years of relevant experience, distinctive skills, level of education attained, certifications or other professional licenses held, and the location of residence and/or place of employment. Base pay is one component of Metropolis's total compensation package, which may also include access to or eligibility for healthcare benefits, a 401(k) plan, short-term and long-term disability coverage, basic life insurance, a lucrative stock option plan, bonus plans, and more.

Who we are

The real world is the next frontier, and at Metropolis, we are creating the artificial intelligence to make it responsive. We are pioneering the Recognition Economy — a future where mundane repetition disappears and being known unlocks access, comfort and belonging everywhere you go. From transforming parking into a seamless drive-in, drive-out experience for millions of Members to expanding our intelligence layer across retail and hospitality, we are building a world that feels instinctive and magical. The future isn’t coming; it’s here, and we need builders, innovators and problem solvers to help us create it.

Who you are

We are seeking a Senior Software Engineer, Backend, to join our Advanced Technologies team. In this role, you will design, develop, and maintain scalable backend systems that integrate cutting-edge hardware with advanced machine learning to understand the behavior of objects in the real world. You'll work with a modern tech stack, including AWS, Java, Scala, gRPC and Protobuf, Redis, MySQL, PostgreSQL, Kubernetes, and Kafka, to deliver high-performance, reliable services. If you are excited about solving complex technical challenges and working at the intersection of distributed systems, real-time data processing, and scalable infrastructure, we would love to hear from you.

What you'll do

• Build robust, scalable, and maintainable backend services in Java and Scala to support mission-critical operations
• Design and implement gRPC APIs to enable high-performance, real-time data transfer between services
• Leverage Redis and MySQL for efficient data storage and retrieval, ensuring reliability and low-latency access
• Deploy and manage microservices on Kubernetes, optimizing for scalability, resilience, and cost efficiency
• Work with Kafka to build scalable, event-driven architectures for real-time data streaming and processing
• Partner with Hardware, Machine Learning, and Operations teams to ensure seamless integration across the ecosystem and provide appropriate tooling
• Analyze and address bottlenecks in performance and scalability while maintaining a focus on system reliability and data integrity

What we're looking for

• Bachelor's or Master's degree in Computer Science, Software Engineering, or a related field
• 8+ years of experience in backend development, preferably within platform or core services
• Proven expertise in industry-standard programming languages, preferably Java and Scala
• Experience building gRPC APIs for efficient and reliable communication between services
• Strong understanding of database design and optimization using Redis and MySQL
• Familiarity with container orchestration and scaling using Kubernetes
• Hands-on experience with Kafka for event-driven architectures
• Exceptional analytical skills with a proven ability to tackle complex technical problems and design innovative solutions
• A team player with excellent communication skills, a learning mindset, and a proactive approach to working across teams

While not required, these are a plus:

• Exposure to frontend integration with frameworks like Next.js

4 Days in Office: Metropolis values in-person collaboration to drive innovation, strengthen culture, and enhance the Member experience. Our corporate team members hold to our office-first model, which requires employees to be on-site at least four days a week, fostering organic interactions that spark creativity and connection.

When you join Metropolis, you’ll join a team of world-class product leaders and engineers, building an ecosystem of technologies at the intersection of parking, mobility, and real estate. Our goal is to build an inclusive culture where everyone has a voice and the best idea wins. You will play a key role in building and maintaining this culture as our organization grows. The anticipated base salary for this position is $170,000.00 USD to 200,000.00 USD annually. The actual base pay offered is determined by a number of variables, including, as appropriate, the applicant's qualifications for the position, years of relevant experience, distinctive skills, level of education attained, certifications or other professional licenses held, and the location of residence and/or place of employment. Base pay is one component of Metropolis’s total compensation package, which usually includes: healthcare benefits, a 401(k) plan, short-term and long-term disability coverage, basic life insurance, a lucrative stock option plan, bonus plans, and more. #LI-NM1 #LI-Onsite

Who we are

Metropolis is an artificial intelligence company that uses computer vision technology to enable frictionless, checkout-free experiences in the real world. Today, we are reimagining parking to enable millions of consumers to just "drive in and drive out." We envision a future where people transact in the real world with a speed, ease, and convenience that is unparalleled, even online. Tomorrow, we will power checkout-free experiences anywhere you go to make the everyday experiences of living, working, and playing remarkable, giving us back our most valuable asset, time.

Who you are

Metropolis is seeking a Staff Software Engineer for our “Network Expansion” team. You will play a key role in building new functionality to support our expansion into new mobility verticals and larger, more complex parking markets. This role requires an individual who thrives in fast-paced environments, working both cross-functionally with product, design, and operations as well as working across multiple engineering teams. 

What you'll do

• Provide technical direction that influences the entire company by formulating and implementing a technical vision and roadmap
• Lead large, cross-team initiatives through the entire development lifecycle, from ideation and requirements through successful launch
• Lead multiple engineering teams (10-15 engineers) towards a common goal
• Work cross-functionally with designers and product managers to understand, model, and solve real-world problems
• Own the outcomes! You’re responsible for real-world metrics shifts and company-defining business outcomes, not just for shipping software 
• Moderate technical discussions, evaluate new techniques, and ensure our platform is constantly evolving and improving
• Leverage best practices in automation testing and deployment to enable rapid iteration and launch of new features
• Help build a culture where bugs and mistakes in Production are treated as opportunities to improve the platform
• Be a great coach to bring the best out of our engineers and a key driver of hiring top talent

What we're looking for

• MS or BS in Computer Science or equivalent work experience. Strong fundamental computer science skills
• 10+ years of experience building customer-centric applications and products
• Proven track record of designing and delivering distributed systems and software products in consumer-facing applications
• Experience with microservices, event-driven architectures, and related technologies and paradigms
• Experience with Agile engineering processes that support the entire software development life cycle, including TDD/BDD, CI/CD, and related build/test/deploy processes
• Experience with database technologies, especially MySQL and Postgres.
• Excellent written and verbal communication skills with a proven ability to present complex technical information clearly and concisely to a variety of audiences
• Track record of successful cross-functional collaboration while building customer solutions in B2C and B2B settings
• Experience succeeding in situations with high levels of ambiguity
• Able to work in the office in one of Santa Monica (Los Angeles), New York City, or Seattle

While not required, these are a plus:

• Advanced-level knowledge of Scala
• An advanced degree in a technical field, such as computer science
• Previous experience working inside innovative, high-growth environments
• Experience with leveraging AI technology to streamline engineering activities

Our Stack

• Languages + Frameworks: TypeScript, React, Scala (principally), Java (limited)
• Datastores: MySQL, PostgreSQL, Snowflake
• Cloud: AWS
• Version control: Git & GitHub
• AI Tooling: Copilot on GitHub and Claude Code
• Observability: Datadog

4 Days in Office: Metropolis values in-person collaboration to drive innovation, strengthen culture, and enhance the Member experience. Our corporate team members hold to our office-first model, which requires employees to be on-site at least four days a week, fostering organic interactions that spark creativity and connection.

When you join Metropolis, you'll join a team of world-class product leaders and engineers, building an ecosystem of technologies at the intersection of parking, mobility, and real estate. Our goal is to build an inclusive culture where everyone has a voice and the best idea wins. You will play a key role in building and maintaining this culture as our organization grows. The anticipated base salary for this position is $220,000 USD to $250,000 USD annually. The actual base pay offered is determined by several variables, including, as appropriate, the applicant's qualifications for the position, years of relevant experience, distinctive skills, level of education attained, certifications or other professional licenses held, and the location of residence and/or place of employment. Base pay is one component of Metropolis's total compensation package, which may also include access to or eligibility for healthcare benefits, a 401(k) plan, short-term and long-term disability coverage, basic life insurance, a lucrative stock option plan, bonus plans, and more.

Who we are

The real world is the next frontier, and at Metropolis, we are creating the artificial intelligence to make it responsive. We are pioneering the Recognition Economy — a future where mundane repetition disappears and being known unlocks access, comfort and belonging everywhere you go. From transforming parking into a seamless drive-in, drive-out experience for millions of Members to expanding our intelligence layer across retail and hospitality, we are building a world that feels instinctive and magical. The future isn’t coming; it’s here, and we need builders, innovators and problem solvers to help us create it.

Who you are

We are seeking a Senior Software Engineer, Backend, to join our Advanced Technologies team. In this role, you will design, develop, and maintain scalable backend systems that integrate cutting-edge hardware with advanced machine learning to understand the behavior of objects in the real world. You'll work with a modern tech stack, including AWS, Java, Scala, gRPC and Protobuf, Redis, MySQL, PostgreSQL, Kubernetes, and Kafka, to deliver high-performance, reliable services. If you are excited about solving complex technical challenges and working at the intersection of distributed systems, real-time data processing, and scalable infrastructure, we would love to hear from you.

What you'll do

• Build robust, scalable, and maintainable backend services in Java and Scala to support mission-critical operations
• Design and implement gRPC APIs to enable high-performance, real-time data transfer between services
• Leverage Redis and MySQL for efficient data storage and retrieval, ensuring reliability and low-latency access
• Deploy and manage microservices on Kubernetes, optimizing for scalability, resilience, and cost efficiency
• Work with Kafka to build scalable, event-driven architectures for real-time data streaming and processing
• Partner with Hardware, Machine Learning, and Operations teams to ensure seamless integration across the ecosystem and provide appropriate tooling
• Analyze and address bottlenecks in performance and scalability while maintaining a focus on system reliability and data integrity

What we're looking for

• Bachelor's or Master's degree in Computer Science, Software Engineering, or a related field
• 8+ years of experience in backend development, preferably within platform or core services
• Proven expertise in industry-standard programming languages, preferably Java and Scala
• Experience building gRPC APIs for efficient and reliable communication between services
• Strong understanding of database design and optimization using Redis and MySQL
• Familiarity with container orchestration and scaling using Kubernetes
• Hands-on experience with Kafka for event-driven architectures
• Exceptional analytical skills with a proven ability to tackle complex technical problems and design innovative solutions
• A team player with excellent communication skills, a learning mindset, and a proactive approach to working across teams

While not required, these are a plus:

• Exposure to frontend integration with frameworks like Next.js

4 Days in Office: Metropolis values in-person collaboration to drive innovation, strengthen culture, and enhance the Member experience. Our corporate team members hold to our office-first model, which requires employees to be on-site at least four days a week, fostering organic interactions that spark creativity and connection.

When you join Metropolis, you’ll join a team of world-class product leaders and engineers, building an ecosystem of technologies at the intersection of parking, mobility, and real estate. Our goal is to build an inclusive culture where everyone has a voice and the best idea wins. You will play a key role in building and maintaining this culture as our organization grows. The anticipated base salary for this position is $170,000.00 USD to 200,000.00 USD annually. The actual base pay offered is determined by a number of variables, including, as appropriate, the applicant's qualifications for the position, years of relevant experience, distinctive skills, level of education attained, certifications or other professional licenses held, and the location of residence and/or place of employment. Base pay is one component of Metropolis’s total compensation package, which usually includes: healthcare benefits, a 401(k) plan, short-term and long-term disability coverage, basic life insurance, a lucrative stock option plan, bonus plans, and more. #LI-NM1 #LI-Onsite

What we do

Our Lead Senior Staff Software Engineers are end-to-end owners who will participate in all aspects of designing, building, and delivering the foundational experiences that make The Trade Desk platform exceptional for the traders who rely on it every day.

The Desk Fundamentals team sits within the Core Workflows engineering organization and owns the platform UI framework that the rest of our buying-side engineering teams build on top of. Our mission is straightforward but demanding: deliver consistent experiences, logical navigation, and user-friendly page components at platform scale. We own the shared design patterns and frontend frameworks that empower other teams to ship features quickly and reliably. We build and evolve the Portfolio Views that give traders clarity into performance across partners and advertisers. We maintain the Programmatic Table — one of the highest-traffic surfaces on the platform — and we are the team that sets the bar for what quality looks like across The Trade Desk's core product.

At The Trade Desk, we believe that each opportunity to engage with all internal and external stakeholders is unique. This means that based on your interests and background, you will have the opportunity to work on large-scale, distributed systems — for example, coordinating thousands of servers in cloud and physical data centers around the world, petabyte-scale data challenges, advanced data visualizations, and interactive user interfaces, to name a few.

Our system performs every day, 24/7, serving global traffic. It's important that we focus on quality at scale in an agile environment based on collaboration, ownership, and trust. Our software engineering teams fully own their charter to work on long-term roadmaps while enhancing existing features or tools and continuously improving efficiency.

What you’ll do

It's the best of both worlds — you'll get a chance to exercise your technical leadership and build up your people management and leadership skills. Some of the work that you will be doing to help us deliver on our mission includes the following:

Technical leadership

• Actively review designs, code, and architecture across the team's surface area, from the platform framework to the data-rich tables and panels that traders use every day.

• Deliver meaningful, technical, and hands-on contributions to the team's objectives, from architectural decisions on our shared UI framework to concrete pull requests.

• Understand strategic business priorities and communicate with the team on how their work connects to the broader roadmap and company goals.

• Drive the technical direction for how other engineering teams within Core Workflows — and across the broader organization — build on top of the platform framework the Desk Fundamentals team owns.

Project level processes and execution

• Collaborate with the PM team to develop the roadmap and MVP plans, translating complex UX and platform consistency challenges into clearly scoped, executable engineering work.

• Develop execution plans including resources, milestones, and timelines for roadmap initiatives.

• Define and track the business KPIs and user-facing metrics that connect the team's engineering work to meaningful outcomes, ensuring the team understands the impact of what they ship.

• Continuously analyze and optimize team efficiency, removing blockers and ensuring the team ships with quality.

• Establish and deliver on team commitments, and communicate important developments and changes to area leadership and other stakeholders.

• Measure and maintain the quality of the team's contributions, including platform reliability, consistency, and developer experience for the teams building on top of what we own.

People management

• Manage a small team of talented engineers, serving as both their technical leader and their people manager.

• Help team members develop career growth plans and accelerate toward their next level.

• Give regular and effective feedback, and hold weekly 1:1 meetings with direct reports.

• Conduct annual reviews and make compensation recommendations.

• Foster an inclusive, psychologically safe team culture where diverse perspectives are genuinely valued.

Who you are

Our culture is much deeper than just having fun together (though we do that well, too). We take pride in our engineers being trust-builders, generous givers, scrappy problem solvers, and gritty pursuers of excellence. You do not have to meet all the requirements below, but we believe that people who meet most of them will have a higher likelihood of succeeding in this role:

• You have a solid understanding of SDLC (Software Development Life Cycle), DevOps, and agile methodologies.

• You have a solid understanding of cloud computing and the trade-offs of large-scale, distributed web applications.

• You have a solid understanding of design patterns and software architecture, including frontend systems design and component-based architectures.

• You have experience contributing to the professional growth of software engineers, and a proven track record of growing multiple senior engineers and tech leads.

• You have experience providing technical and project leadership of initiatives involving multiple teams, including platform or framework work where your team's decisions directly affect the velocity and quality of teams outside your own.

• You have experience leading and completing projects with a high degree of technical ambiguity.

• You have experience driving major, strategic, company-wide initiatives with significant risk.

• You have experience hiring and conducting interviews.

• You are proficient in one or more of the following programming languages: TypeScript/JavaScript, C#, Java, C, C++, Python, SQL, or Scala.

• You have 13+ years of software development engineering experience.

• You have 1+ years of experience directly managing people.

• You have a Bachelor's/Master's level degree in computer science or a relevant engineering-related field, or equivalent experience. Not everyone has the same level of access to opportunities. What is most important to us is what and how you can contribute, which is why our consideration is not limited by the level of education you have.

• You have additional nice-to-have experience in the following areas: full-stack web development, frontend framework design, data visualization and table-heavy UI systems, distributed systems, microservices, Kubernetes, and AI/LLM integration into production applications.

We are a global team with different backgrounds, experiences, and perspectives. To complement this team, you will welcome ideas that are different from your own and be well-versed in building from common ground to value, seek out, and foster invisible and visible dimensions of diversity.

A variety of technical opportunities is one of the best things about working at The Trade Desk as a software engineer, which is why we do not expect you to know every technology we use when you start. What we care about is that you can learn quickly and find solutions to complex problems using the optimum tools for the job. What you know is less important than how well you learn and innovate. We are not seeking engineers who know all the answers; we need engineers who can invent answers no one has thought of yet and find answers to the questions yet to be asked.

The Trade Desk does not accept unsolicited resumes from search firm recruiters. Fees will not be paid in the event a candidate submitted by a recruiter without an agreement in place is hired; such resumes will be deemed the sole property of The Trade Desk. The Trade Desk is an equal opportunity employer. All aspects of employment will be based on merit, competence, performance, and business needs. We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, veteran status, or any other status protected under federal, state, or local law.

Riot’s Data Engineers harness petabytes of data and state-of-the-art processing technologies to build products that elevate the player experience at massive scale. Turning this data into meaningful insights is a complex challenge, and our engineers meet it by staying deeply player-focused and collaborating across diverse teams to improve the lives of millions of players worldwide.

As a Senior Engineering Manager for Data Engineering within the PubSports vertical, you will lead the evolution of PubSports’ data platform capabilities by operationalizing Riot’s data platform architecture, governance standards, and maturity frameworks. This role is responsible for modernizing PubSports’ data ecosystem and ensuring that data assets supporting player engagement, monetization, and insights are reliable, scalable, and aligned with Riot’s enterprise data platform standards. You will operate within Riot’s emerging Data Platform operating model, translating platform architecture and governance frameworks into production-grade data systems that deliver trusted insights and enable advanced analytics, experimentation, and machine learning. This role will also grow and lead a team of data engineers responsible for delivering durable data products that power analytics, business intelligence, and ML-driven player experiences.

Responsibilities:

• Lead modernization of PubSports data pipelines and architecture 
• Implement and enforce medallion/lakehouse standards 
• Eliminate duplicate or fragmented data workflows 
• Ensure scalable, modular, and reusable system design 
• Drive reduction of tech debt and legacy instability 
• Establish SLIs/SLOs for critical datasets 
• Drive clear dataset ownership and operational accountability 
• Improve data quality monitoring and incident response discipline 
• Align vertical standards with enterprise practices 
• Partner closely with PubSports Product Insights to translate business requirements into durable datasets 
• Accelerate time-to-insight through well-designed curated layers 
• Ensure semantic clarity and standardized business metrics 
• Support analytics, BI, and ML use cases with production-grade data foundations 
• Operationalize Riot’s data maturity and governance frameworks 
• Lead and grow a high-performing team of Data Engineers 
• Drive predictable sprint execution and roadmap alignment 
• Maintain high code quality and review rigor 
• Coach engineers on scalable system design and data modeling 
• Balance speed with architectural integrity 

Required Qualifications:

• 10+ years in data engineering or data platform roles 
• 5+ years leading DE teams in production environments 
• Deep expertise in Spark / Databricks 
• Deep, production-level expertise in a major data engineering programming language such as Python or Scala
• Advanced SQL and dimensional modeling, Orchestration (Airflow or similar), Lakehouse / medallion architecture 
• Proven experience designing and implementing real-time/streaming data pipelines using technologies like Kafka, Flink, or similar platforms 
• Deep Experience in Data quality & monitoring frameworks 
• Working knowledge of cloud-native data services (e.g., AWS/GCP/Azure) and a track record of data platform cost optimization and resource management. 
•  Expertise in data security and privacy engineering, including the implementation of robust access control (RBAC/ABAC) and data masking/anonymization techniques. 
• Proven experience modernizing legacy systems 
• Demonstrated ability to translate business needs into scalable technical solutions 

Desired Qualifications: 

• Experience in gaming, large consumer platforms, or systems leading data modernization or transformation initiatives in a complex environment 
• Track record improving data maturity ( e.g. SLI’s/SLO governance, reliability standards) Experience designing semantic layers or standardized business metric frameworks 
• Background supporting advanced analytics use cases in high velocity product environments 
• Demonstrated ability to influence standards across teams in a matrixed organization

For this role, you'll find success through craft expertise, a collaborative spirit, and decision-making that prioritizes your fellow Rioters, who are the customers of your work. Being a dedicated fan of games is not necessary for this position!

Our Perks:

Riot focuses on work/life balance, shown by our open paid time off policy and other perks such as flexible work schedules. We offer medical, dental, and life insurance, parental leave for you, your spouse/domestic partner, and children, and a 401k with company match. Check out our benefits pages for more information.

At Riot Games, we put players first. That mission drives every decision in our quest to create games and experiences that make it better to be a player. Whether you’re working directly on a new player-facing experience or you’re supporting the company as a whole, everyone at Riot is part of our mission. And just like in our games, we’re better when we work together. Our goal is to create collaborative teams where you are empowered to bring your unique perspective everyday. If that sounds like the kind of place you want to work, we’re looking forward to your application.

It’s our policy to provide equal employment opportunity for all applicants and members of Riot Games, Inc. Riot Games makes reasonable accommodations for handicapped and disabled Rioters and does not unlawfully discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, handicap, veteran status, marital status, criminal history, or any other category protected by applicable federal and state law. We consider for employment all qualified applicants, including those with criminal histories, in a manner consistent with applicable federal, state and local law, including the California Fair Chance Act, the City of Los Angeles Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, the San Francisco Fair Chance Ordinance, and the Washington Fair Chance Act.

Per the Los Angeles County Fair Chance Ordinance, the following core duties may create a basis for disqualifying candidates with relevant criminal histories:

• Safeguarding confidential and sensitive Company data
• Communication with others, including Rioters and third parties such as vendors, and/or players, including minors
• Accessing Company assets, secure digital systems, and networks
• Ensuring a safe interactive environment for players and other Rioters

These duties are directly related to essential operations, safety, trust, and compliance obligations within our organization. Please note that job duties may evolve based on business needs and additional responsibilities may be assigned as necessary to maintain operational efficiency and security. 

CSQ127R318

As a Big Data Solutions Architect (Resident Solutions Architect) in our Professional Services team you will work with clients on short to medium term customer engagements on their big data challenges using the Databricks platform. You will provide data engineering, data science, and cloud technology projects which require integrating with client systems, training, and other technical tasks to help customers to get most value out of their data. RSAs are billable and know how to complete projects according to specification with excellent customer service. You will report to the regional Manager/Lead.

The impact you will have:

• You will work on a variety of impactful customer technical projects which may include designing and building reference architectures, creating how-to's and productionalizing customer use cases
• Work with engagement managers to scope variety of  professional services work with input from the customer
• Guide strategic customers as they implement transformational big data projects, 3rd party migrations, including end-to-end design, build and deployment of industry-leading big data and AI applications
• Consult on architecture and design; bootstrap or implement customer projects which leads to a customers' successful understanding, evaluation and adoption of Databricks.
• Provide an escalated level of support for customer operational issues.
• You will work with the Databricks technical team, Project Manager, Architect and Customer team to ensure the technical components of the engagement are delivered to meet customer's needs.
• Work with Engineering and Databricks Customer Support to provide product and implementation feedback and to guide rapid resolution for engagement specific product and support issues.

What we look for:

• 6+ years experience in data engineering, data platforms & analytics
• Comfortable writing code in either Python or Scala
• Working knowledge of two or more common Cloud ecosystems (AWS, Azure, GCP) with expertise in at least one
• Deep experience with distributed computing with Apache Spark™ and knowledge of Spark runtime internals
• Familiarity with CI/CD for production deployments
• Working knowledge of MLOps 
• Design and deployment of performant end-to-end data architectures
• Experience with technical project delivery - managing scope and timelines.
• Documentation and white-boarding skills.
• Experience working with clients and managing conflicts.
• Build skills in technical areas which support the deployment and integration of Databricks-based solutions to complete customer projects.
• Travel to customers 20% of the time
• Databricks Certification