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House Keeping Janitorial in San Francisco

8 active opportunities · Updated October 2026

Explore current house keeping janitorial jobs in San Francisco. Filter by work mode, employment type, experience, department, date posted and distance.

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

$150K – $230K/yr

Quick readStrong listing-quality and freshness signals

Sigma Computing is seeking an experienced employment counsel to provide legal guidance on all aspects of employment law across the organization. This role will partner closely with People Operations, leadership, and business teams to manage risk, ensure compliance, and support a positive employee experience in a fast-paced, high-growth technology environment. Key Responsibilities Provide legal advice on employment-related matters including onboarding, performance management, disciplinary actions, terminations, and reductions in force; Ensure compliance with federal, state, and local employment laws and regulations (U.S. and, if applicable, international); Draft, review, and update employment agreements, offer letters, contractor agreements, policies, and handbooks; Advise on employee relations issues and dispute resolution; Manage and oversee outside employment counsel and litigation matters; Complete workplace investigations; Partner with People Ops (HR) and Governance, Risk, & Compliance (GRC) teams on compliance training, and policy implementation; Monitor changes in employment law and proactively recommend updates to company practices; Support M&A, due diligence, and integration efforts related to employment matters as needed. Qualifications Juris Doctor (JD) from an accredited law school; Active license to practice law in at least one U.S. jurisdiction; 5+ years of experience practicing employment law (in-house experience at a technology or SaaS company preferred); Workplace investigation training and experience; Strong knowledge of U.S. employment laws (FLSA, ADA, FMLA, Title VII, wage & hour, classification, etc.); Ability to provide practical, business-oriented legal advice is essential; Workplace investigation training and experience; Experience working closely with HR/People teams and senior leadership; and Excellent communication, judgment, and stakeholder management skills. Preferred Qualifications Experience s

PythonSQLAWSAI
L
📍 San Francisco, Canada· Full-time
✓ High-confidence listingCompany trend -74%
Quick readStrong listing-quality and freshness signals

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. Lyft is hiring an experienced, talented and energetic M&A lawyer to join our expanding Legal team. You will lead a broad range of corporate and transactional matters and provide effective, business-focused legal advice to stakeholders throughout Lyft. Our legal work is cutting edge and always evolving. Reporting into the VP, Deputy General Counsel, Corporate & Commercial, we are looking for an entrepreneurial, resourceful, and highly collaborative leader who can continuously assess and advise on legal issues using a creative and pragmatic approach. Responsibilities: Lead a wide range of corporate initiatives, including complex M&A and integrations, divestitures, strategic investments, joint ventures, domestic and international corporate structuring, capital markets transactions, financing matters, subsidiary management and other strategic corporate projects. Manage and mentor a high-performing in-house team of M&A legal professionals, fostering a culture of growth and execution excellence. Partner closely with Lyft’s Corporate Development team and Treasury team as well as advise company leadership and cross-functional stakeholders (e.g. people, accounting, tax, treasury, operations, etc.) on novel corporate legal issues, opportunities and risks of corporate transactions. Draft and negotiate NDAs, LOIs/term sheets and definitive transaction agreements. Shape, scale and improve our legal processes/playbooks that enable both legal and business functions to scale effectively. Assist other teams with projects on an as-needed basis. Experience: 10+ years of experience practicing corporate and securities law, with an emphasis on M&A and strategic transactions; experience at a top-tier law firm and in-house experience at a public company are both required. Degree from top-tier law s

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

From $1.6M/yr

Quick readStrong listing-quality and freshness signals

About the Team The Spark Platform team owns and operates DoorDash's Apache Spark ecosystem — the execution runtime, remote shuffle service, cluster scheduler, and reliability tooling that powers the company's data, analytics, and ML workloads. We run Spark across the company at significant scale and continue to expand the workloads, capabilities, and consumer base we serve. Orchestrating and operating thousands of Spark cluster deployments is a complex distributed system problem which the team invests heavily in runtime optimization, systems architecture, multi-tenant scheduling, and end-user tooling. About the Role As a Software Engineer on Spark Platform, you will execute across the surfaces of our in-house Spark deployment that serves the entire company. The work spans Spark runtime upgrades and performance, multi-tenant scheduling and executor bin-packing on Kubernetes, cluster lifecycle automation, and the observability and incident automation that keep the platform sustainable. You will move between layers as the work demands — picking up the next high-leverage problem regardless of where it sits — and partner closely with the rest of the team and with platform consumers across the company. You must be located in San Francisco, Sunnyvale, Seattle, or New York City for this hybrid position. You will report into the Engineering Manager on our Spark Platform team. You're excited about this opportunity because you will… Build and operate an in-house Spark platform that runs at company-wide scale, spanning runtime, scheduler, reliability, and user-facing tooling. Drive multi-tenant scheduling, executor bin-packing, and cost-aware placement that let a small team serve dozens of consumer teams. Own pieces of cluster lifecycle automation — provisioning, upgrades, capacity changes, and node-failure handling — at a scale where these stop being manual events. Build the observability and incident automation that make the platform debuggable end-to-end and keep on-call sus

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

From $1.6M/yr

Quick readStrong listing-quality and freshness signals

About the Team The Spark Platform team owns and operates DoorDash's Apache Spark ecosystem — the execution runtime, remote shuffle service, cluster scheduler, and reliability tooling that powers the company's data, analytics, and ML workloads. We run Spark across the company at significant scale and continue to expand the workloads, capabilities, and consumer base we serve. Orchestrating and operating thousands of Spark cluster deployments is a complex distributed system problem which the team invests heavily in runtime optimization, systems architecture, multi-tenant scheduling, and end-user tooling. About the Role As a Senior Software Engineer on Spark Platform, you will set the technical direction for our in-house Spark deployment and shape the architecture that will run DoorDash's data, analytics, and ML compute for the next five years and beyond. You will own the deep, cross-cutting problems that span the runtime, the shuffle service, the scheduler, and the overall service reliability — making the architectural calls that compound across the platform's lifetime. You will partner with the Engineering Manager on technical roadmap, hiring, and team shape, and act as the senior technical voice in cross-team partnerships with Data Engineering, ML Platform, and product engineering teams that depend on the platform. You must be located in San Francisco, Sunnyvale, Seattle, or New York City for this hybrid position. You will report into the Engineering Manager on our Spark Platform team. You're excited about this opportunity because you will… Set the multi-year technical direction for an in-house Spark-on-Kubernetes platform — runtime, shuffle, scheduler, reliability — and make the architectural calls that compound for years. Own the deepest distributed-systems problems on the team: shuffle architecture, multi-tenant scheduling, runtime performance, and the failure modes that only show up at scale. Partner with the Engineering Manager on technical roadmap, hiring, inte

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

Amplitude is the leading AI analytics platform, helping over 4,700 customers—including Atlassian, Burger King, NBCUniversal, and Square—build better products and digital experiences. With powerful AI Agents embedded across our platform, teams can analyze, test, and optimize user experiences faster than ever. Ranked #1 across multiple categories in G2’s Winter 2026 Report, Amplitude is the best-in-class solution for product, data, and marketing teams. Learn more at amplitude.com . As an organization, we deliver for our customers by living our values. We operate from a place of humility, take ownership of problems and successes, approach challenges with a growth mindset, and put our customers at the center of everything we do. Amplitude’s Commitment to Diversity Equity & Inclusion (DEI): Amplitude believes that diversity enables the creation of better products, improves the ability to solve complex problems, and drives more powerful solutions. We strive to create an environment of inclusion—one focused on psychological safety, empathy, and human connection—that will allow employees of all backgrounds to thrive. About the Role & Team Every AI insight, every experiment, every cohort at Amplitude starts with a query. Our in-house OLAP engine, Nova , processes trillions of events in real time — turning raw behavioral data into fast, trustworthy answers that power decisions for thousands of product teams worldwide. We're entering a world where AI agents don't just assist product teams — they ship features, run experiments, and make prioritization calls autonomously. What makes that possible is agents' ability to verify their work against real product data continuously. That makes Nova the critical infrastructure in the loop, and as non-stop agents become the main source of queries, the demand on Nova's throughput, correctness, and operational rigor grows dramatically. We're looking for a Senior Software Engineer who wants to go deep on the engine internals and the

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

Amplitude is the leading AI analytics platform, helping over 4,700 customers—including Atlassian, Burger King, NBCUniversal, and Square—build better products and digital experiences. With powerful AI Agents embedded across our platform, teams can analyze, test, and optimize user experiences faster than ever. Ranked #1 across multiple categories in G2’s Winter 2026 Report, Amplitude is the best-in-class solution for product, data, and marketing teams. Learn more at amplitude.com . As an organization, we deliver for our customers by living our values. We operate from a place of humility, take ownership of problems and successes, approach challenges with a growth mindset, and put our customers at the center of everything we do. Amplitude’s Commitment to Diversity Equity & Inclusion (DEI): Amplitude believes that diversity enables the creation of better products, improves the ability to solve complex problems, and drives more powerful solutions. We strive to create an environment of inclusion—one focused on psychological safety, empathy, and human connection—that will allow employees of all backgrounds to thrive. About the Role & Team Every AI insight, every experiment, every cohort at Amplitude starts with a query. Our in-house OLAP engine, Nova , processes trillions of events in real time — turning raw behavioral data into fast, trustworthy answers that power decisions for thousands of product teams worldwide. We’re entering a world where AI agents don’t just assist product teams — they ship features, run experiments, and make prioritization calls autonomously. What makes that possible is agents’ ability to verify their work against real product data continuously. That makes Nova the critical infrastructure in the loop, and as non-stop agents become the main source of queries, the demand on Nova’s throughput, correctness, and operational rigor grows dramatically. We’re looking for a Staff Software Engineer who wants to go deep on both the engine internals and

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

#Team Nextdoor Nextdoor is where you connect to the neighborhoods that matter to you so you can belong. Our purpose is to cultivate a kinder world where everyone has a neighborhood they can rely on. Neighbors around the world turn to Nextdoor daily to receive trusted information, give and get help, get things done, and build real-world connections with those nearby — neighbors, businesses, and public services. Today, neighbors rely on Nextdoor in more than 350,000 neighborhoods across 11 countries. Meet your Future Neighbors As an Analytics Engineer 4 with Nextdoor, Inc. (San Francisco, CA) (May telecommute from any U.S. location) you’ll: Apply mathematical or statistical theory and methods to design, create, and select the appropriate samples of data that will allow the data science team to conduct probabilistic experiments and statistical analyses Design software systems and processes to gather data in the most efficient way and determine key data points needed in order to interpret experiment results and ensure results are properly tracked Interpret data and report conclusions drawn from their analyses Work with cross-functional teams, including product, design, engineering, marketing, operations, and sales, to determine which data analyses will lead to the most actionable insights Build data pipelines to create and transform data for analysis of different product features Clean and summarize data to make it accessible for reporting and for data science Combine data from multiple sources to make and distribute client reports in order to see how particular ad products are performing Analyze expected vs actual delivery of ad products in order to find and improve gaps in our delivery pipeline What You’ll Bring to The House Master’s degree or foreign equivalent in Mathematics, Statistics, Business Analytics, or closely related quantitative field. Three (3) years of years of experience in the role or in a related position. Full term of experience m

PythonSQLAIRust
L
📍 San Francisco, Canada· Full-time
✓ High-confidence listingCompany trend -74%
Quick readStrong listing-quality and freshness signals

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. Lyft Ads is one of the fastest-growing commerce media businesses in the industry, connecting brands to a high-intent, on-the-move audience across Lyft's rider and driver networks. With proprietary first-party data spanning millions of rides and real-world consumer journeys, Lyft Ads offers advertisers a unique combination of targeting, context, and measurement that traditional platforms cannot replicate. We are building the future of mobility media — and we are looking for exceptional talent to help lead that charge. We are seeking a strategic, highly cross-functional leader to join Lyft Ads as our Sr. Product Marketing Manager for Measurement, Data & Audiences. This is a unique and high-impact role at the intersection of data commercialization, advanced measurement strategy, and go-to-market execution. As the direct commercial counterpart to our Ad Infrastructure Product Management team , you will translate back-end data signals, in-house attribution models, and reporting tools into compelling, market-facing solutions. You will own the strategy for how Lyft Ads packages and positions its first-party mobility data, validates performance through third-party measurement partners, and delivers trusted ROI clarity to brands and agencies. Additionally, you will lead the identification, evaluation, and commercialization of custom, bespoke data partnerships that unlock strategic value and incremental revenue streams for Lyft Ads. This role requires a rare blend of technical data literacy, commercial acumen, and operational execution. You will work closely with Product, Data Science, Engineering, Sales, and external partners to define how Lyft Ads goes to market and proves its value in the rapidly evolving commerce media landscape Responsibilities: Data Commercialization & Audience

GitAIGoRust
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