Top Natural Language Processing Jobs in Los Angeles, CA

Own Whippy’s messaging, lifecycle and email marketing, HubSpot operations, customer proof and case studies, event campaigns, partner enablement, retargeting, attribution, and pipeline generation. The role combines hands-on product marketing with demand generation, requiring ownership from positioning through campaign execution and measurement. It also manages the content writer and helps turn founder-led content into repeatable marketing assets and revenue-producing motions.

Partner with enterprise financial firms to design and implement scalable practice management programs. Lead executive engagement, success roadmapping, content and curriculum development, and live facilitation. Drive adoption through program design, data-driven recommendations, and feedback to Product. Travel regularly to client sites and industry events to deliver sessions and represent Zocks as a subject-matter expert.

Lead enterprise practice management engagements for large RIAs, broker-dealers, banks, and insurers. Design rollout strategies, build scalable enablement programs and content, run discovery workshops, analyze data to recommend operational improvements, and deliver in-person/virtual facilitation and industry presentations. Act as enterprise client voice to product and travel frequently for client meetings and conferences.

Own lifecycle email and in-app campaigns for portfolio products using Iterable and HubSpot. Build, schedule, test, and optimize customer journeys; coordinate cross-functional marketing projects; develop A/B tests; analyze campaign performance; improve execution systems and processes; and support cross-product adoption across Superhuman’s product suite.

Supports Pfizer CentreOne’s inside sales and marketing activities by reviewing and routing marketing-qualified leads, executing outreach sequences, documenting activity in Salesforce, and assisting with campaigns, content, meetings, reporting, and marketing projects. The role develops commercial expertise across marketing, inside sales, and business development while progressing leads toward initial meetings and BD handoff.

Own complex technical support issues from reproduction through resolution, troubleshooting APIs, webhooks, workflows, integrations, and AI agent behavior. Escalate well-documented issues to Engineering, identify recurring patterns, and partner on product improvements. Create runbooks and troubleshooting guides, coach Tier 1/2 and BPO teams, support critical incidents and premier accounts, participate in on-call rotation, and handle sensitive customer data appropriately.

Build and operate Deepgram’s deal desk, including approval matrices, pricing playbooks, credit and promotion guidelines, non-standard deal reviews, pricing analysis, Salesforce CPQ workflows, and audit-ready approvals. Partner with Sales, Customer Success, Product, and Finance on pricing, packaging, renewals, and revenue recognition. Use AI for first-pass deal reviews and continuously improve desk rules and processes.

Supports and maintains enterprise customer web integrations using Smartling’s web proxy solution. Owns technical tickets, troubleshoots browser and network issues, leads customer workshops, creates diagnostic scripts and tooling, manages production configuration changes, and collaborates with Engineering on product fixes. The role requires strong web technologies, debugging, communication, and customer-facing technical consulting skills.

The Sr. Machine Learning Engineer will develop and deploy ML solutions for healthcare, manage data pipelines, and work with large datasets to enhance healthcare delivery.

Leads Getty’s corporate insurance program covering fine art, property, liability, cyber, workers’ compensation, construction, and other risks. Oversees insurance placement, renewals, coverage analysis, claims, valuations, contractual risk allocation, broker and carrier relationships, and compliance. Partners with Legal, HR, Facilities, Security, museums, and leadership while managing a small team and optimizing coverage, costs, deductibles, and claims outcomes.

Build and operate the platform that schedules, runs, and monitors machine learning training, evaluation, and reinforcement-learning workloads on Kubernetes. Responsibilities include job scheduling, workload networking, runtime isolation, checkpoint storage, automation, infrastructure as code, observability, and production troubleshooting. The role collaborates with AI researchers and ML engineers and includes a compensated 24/7 on-call rotation.