Top Tech Jobs & Startup Jobs in Los Angeles, CA

Source, evaluate, clean, label, and organize diverse, high-quality data inputs for a proprietary model. Explore web sources, validate signal and relevance, and help improve processes that turn raw information into usable datasets.

Provide comprehensive service to assigned clients, qualify inbound leads, support advisor team preparation and workflow, document interactions in CRM, coordinate with portfolio management/operations/financial planning, ensure compliance, and help achieve business development and client retention goals.

The Sales Executive will manage marketing and sales of import/export services, generate new business, service accounts, and implement strategies, ensuring proper documentation and customer service.

The Director of Business Development will manage territory sales, develop client relationships, meet sales targets, and collaborate with leadership. Experience in pharma and SaaS is preferred.

The Client Finance Manager manages client relationships, overseeing budgets and financial targets, ensuring projects are within budget, and providing financial reports.

Designs, develops, tests, and deploys scalable batch and streaming data pipelines using Databricks, Python, SQL, and PySpark. Builds ingestion, transformation, governance, monitoring, and data quality frameworks across Azure or AWS environments. Develops analytical data models and CI/CD processes, optimizes Spark performance, troubleshoots deployments, and collaborates with data scientists, analysts, business users, and technical teams. Provides technical leadership, mentoring, documentation, and support in an agile consulting environment.

Leads technical delivery for Salesforce Marketing Cloud engagements, owning solution architecture, data models, integrations, standards, code and configuration review, testing, deployments, and client technical discussions. Builds journeys, automations, data extensions, content, AMPscript, and server-side JavaScript while validating segments and platform capabilities. Uses and governs AI tools for development, documentation, review, and testing. Mentors consultants and supports adoption of Marketing Cloud Next and Data 360.

Lead end-to-end marketing solution architecture for a Salesforce program, including discovery, requirements, journeys, segmentation, consent, data modeling, integrations, testing, and client sign-off. Partner with technical leads across Salesforce Core, Marketing Cloud, Data 360, Agentforce, and enterprise data platforms. Use AI tools to draft and validate requirements and designs, prototype solutions, and review generated work for accuracy. Explain complex solutions to technical and non-technical stakeholders while guiding implementation and change decisions.

Drive new business for an on-demand pay solution by prospecting, demonstrating product value, negotiating and closing deals, and collaborating with marketing, product, and customer success to ensure client satisfaction and retention.

Partners with business leaders to translate strategic priorities into technology strategies, roadmaps, requirements, and scalable solutions. Designs, develops, configures, and supports Salesforce capabilities, integrations, automation, reporting, security, and data models. Evaluates emerging platforms, builds proofs of concept, manages technology initiatives and stakeholders, and ensures solutions address scalability, compliance, privacy, security, and business value. Communicates priorities, risks, progress, and recommendations across business and Technology leadership.

Supports marketing programs including consumer growth, email, social media, events, webinars, and sales enablement. Creates campaign materials and social content, builds outbound sequences, maintains contact lists, tracks campaign performance, prepares reports, coordinates event logistics, and collaborates with Sales, Product, and Customer Success. Uses AI tools for content creation and campaign analysis.

Leads global AI integration across software engineering platforms and manages distributed engineering leaders across three countries. Drives adoption of AI-assisted development tools, modernizes software delivery workflows, oversees security and compliance, and integrates AI into React, .NET, Java, Salesforce, and MuleSoft platforms. Requires extensive software development and senior engineering leadership experience, plus expertise in cloud, SaaS architecture, privacy, tenant isolation, and enterprise AI transformations.

Develop fraud detection and identity-risk machine learning models from problem definition through production deployment. Responsibilities include investigating fraud patterns, exploratory analysis, feature engineering, model training and evaluation, production-quality Python and PySpark development, monitoring model and feature drift, and presenting analytical recommendations. The role requires collaboration with data scientists and engineers while addressing privacy, explainability, validation, governance, and real-world fraud-modeling challenges such as class imbalance and delayed labels.