Top Tech Jobs & Startup Jobs

Lead enterprise model-training strategy for Commercial AI products: fine-tune LLMs (QLoRA/LoRA/PEFT), train traditional ML models, design large-scale data pipelines, enforce data governance and PII handling, build reproducible experiment/training pipelines, optimize GPU/distributed training costs, and mentor teams to operationalize models into production.

The Software Architect will lead AI quality evaluation, design evaluation frameworks, create risk controls, and ensure compliance, partnering with various teams on AI systems.

Lead design and implementation of the enterprise AI orchestration and retrieval platform: build MCP servers, define tool-surface and multi-agent patterns, design RAG systems and chunking, implement routing/context/window management and observability, set evaluation and safety standards, onboard product teams, and mentor engineers to raise orchestration and retrieval maturity.

The Account Executive will manage the full sales process for new customer acquisition in North America, focusing on complex B2B sales cycles while collaborating with SDRs and technical stakeholders.

The Principal Technical Program Manager will lead complex cross-functional initiatives, align teams, manage risks, and communicate updates to senior leadership effectively.

The Principal Software Engineer will design and deliver core services for logistics, driving innovation in API-first microservice architecture using Scala, with a focus on scalable, reliable, high-quality distributed systems.

As a Senior Software Engineer, you'll design and deliver core services in a microservice architecture, focusing on scalability and innovation within a logistics platform for e-commerce.

Lead REO asset management and disposition for a commercial real estate portfolio. Oversee asset managers and analysts, develop disposition and underwriting strategies, monitor budgets, manage CMBS/REMIC nuances, coordinate loan workout transitions, conduct site visits, and drive valuation, due diligence, and sales/leasing activity.

The role involves leading client engagements for AI adoption, shaping practice evolution, and ensuring successful integration of AI into business processes.

Lead CAE and digital validation for canister and fuel delivery module products: develop component-to-system models, translate analytical results into design guidance, manage suppliers and global modeling standards, drive software/method adoption, lead sustainability analytics and automation, and oversee related technical initiatives and team deliverables.

As a Smart Contract Engineer at Ether.fi, you will design and deploy Solidity smart contracts, build decentralized financial systems, and automate on-chain operations while ensuring high code quality and security.

Own paid acquisition end-to-end across Google, LinkedIn, and Meta. Build and scale channels, run rigorous A/B experiments, instrument funnel metrics, optimize creative and landing pages, and report spend, efficiency, and pipeline contribution while collaborating with product marketing, sales, and design.

Architect and build the core frontend for a collaborative cloud platform, focusing on flexible infrastructure and technical roadmap features.

The Product Manager will own the product development lifecycle for key operations modules, focusing on user needs, technical integration, and release management. Responsibilities include roadmap sequencing, PRD writing, and collaborating with engineering and implementation teams.

Sell and service products within an assigned territory by prospecting, calling on customers, conducting quarterly site visits, building relationships, recommending pricing, closing new business, and maintaining sales reporting and product knowledge.

Lead enterprise architecture transformation for a 60-application portfolio: design scalable cloud-native solutions, define API strategy, establish governance, drive build vs. buy decisions, remediate technical debt, integrate AI/GenAI, and align technology investments with business priorities while leading global cross-functional teams and vendors.

Build and evaluate risk models for natural catastrophes and other perils using advanced statistics and machine learning. Analyze large, diverse datasets, validate vendor models, develop internal exposure views, create scalable pipelines, and communicate results to underwriters and stakeholders to inform underwriting decisions.