Top Tech Jobs & Startup Jobs in Los Angeles, CA

Lead the technical direction and hands-on development of ML and operations research systems powering delivery dispatch. Build pricing, quote selection, forecasting, routing, batching, fleet recommendation, LLM, optimization, evaluation, and MLOps capabilities. Translate operational constraints into reliable models and solver formulations, establish production ML standards, and mentor engineers. The role partners with Product and leadership to deliver measurable improvements in revenue, margin, utilization, conversion, and delivery reliability.

Build and own backend services, web applications, REST APIs, webhooks, and enterprise integrations. Lead customer integrations from scoping through launch, improve the operator dashboard, and maintain production reliability through monitoring, incident response, and root-cause analysis. Collaborate with product, success, and customer engineering teams while contributing to code reviews, technical design, mentoring, security, and AI-assisted development.

Leads Burq’s delivery supply strategy, provider relationships, operational performance, team development, budget, and network expansion. Owns service levels, coverage, cost, provider negotiations, performance accountability, and executive reporting. Partners cross-functionally with Customer Success, Sales, Product, Engineering, and Support to align supply with customer needs. Uses provider data and AI tools to monitor network health, automate reporting, and identify operational, process, and technical improvements.

Own the full enterprise sales cycle from prospecting through multi-year deal closure and expansion. Build pipeline, manage executive relationships, conduct discovery, deliver demos and ROI business cases, lead pilots, and navigate procurement, legal, and security reviews. Partner with Product, Operations, and Customer Success for successful launches and expansions while maintaining accurate CRM records, forecasts, and pipeline reports. Provide market insights to guide pricing, messaging, and product priorities.

Own post-sale relationships with merchant and enterprise customers from onboarding through renewal and expansion. Manage account health, retention, QBRs, churn prevention, adoption, and growth while reporting ARR, churn, and NPS. Serve as the customer voice internally, coordinate with cross-functional teams, support product feedback, and build scalable success processes. Use AI tools daily for reporting, account analysis, documentation, and issue triage. Logistics, API integration, and enterprise account experience are required.

Owner of enterprise customer technical and commercial health: debug integrations, trace API/webhook failures, build dashboards with SQL, lead QBRs and renewals, drive expansion and product adoption, create runbooks, and relay technical feedback to Product and Engineering.

Own technical pre-sales for enterprise delivery deals: run discovery, build tailored demos and POCs, guide engineering through API integrations to first live orders, produce integration specs, respond to RFPs/security questionnaires, and hand off to post-sales while informing product roadmap.

Lead finance and operations at a high-growth marketplace startup: own budgeting, forecasting, capital allocation, revenue strategy, FP&A, accounting operations, audit readiness, fundraising diligence, cap table and scenario modeling, and partner with founders on company-wide operational decisions.

Founding member of the Platform team owning infrastructure, security, CI/CD, and reliability. Design and operate AWS account architecture and services (ECS Fargate, RDS/Aurora, ElastiCache, SQS, ALB), author Terraform IaC, harden IAM and S3, enable AWS security tooling, maintain SOC 2 readiness, improve GitHub Actions pipelines, build PR and local dev environments, integrate observability, and lead incident reviews and runbook creation.

Lead and build Burq's data and ML platform: own warehouse, ingestion, semantic layer, and BI; architect and ship forecasting, optimization, matching, and reliability models; implement feature pipelines, training/serving, and monitoring; drive AI agent initiatives; hire and grow a data/ML team; set governance, intake processes, and partner with product, engineering, and commercial stakeholders to align models with business impact.