Top Tech Jobs & Startup Jobs in NYC, NY

Supports the Data Science and Machine Learning team by analyzing large-scale datasets, identifying anomalies and root causes, developing data validation and normalization methods, and improving the accuracy of derived data products. The intern will evaluate models, translate ambiguous problems into statistical formulations, debug messy data, test hypotheses, and implement maintainable analytical solutions using Python, SQL, and distributed data platforms.

Design and maintain scalable services, APIs, distributed systems, and data pipelines for AI training data infrastructure. Own systems through design, implementation, testing, deployment, and monitoring. Lead architectural decisions, improve reliability and scalability, mentor engineers, and collaborate with AI/ML, product, and data operations teams. Contribute to CI/CD, containerization, DevOps, and cloud deployment practices.

Leads the people-side implementation of manufacturing transformation initiatives, including ERP projects and standard costing deployment. Partners with finance, operations, systems teams, and manufacturing sites to embed consistent costing processes, improve data integrity, support margin visibility, and drive adoption of new ways of working. Delivers training, facilitates change, influences stakeholders at all organizational levels, and translates costing policies into practical Microsoft D365 processes.

Senior individual contributor responsible for generating and converting enterprise new-client revenue across North America. Own $10M+ net new targets, personally originate and close complex $5M–$15M engagements, lead C-suite conversations, negotiate high-value agreements, navigate procurement and legal processes, and partner with sales and finance to protect margin and scale enterprise pipeline.

Develop strategic messaging and polished website copy for B2B clients, especially technology, SaaS, cybersecurity, AI, and healthcare companies. Responsibilities include creating positioning frameworks, value propositions, messaging pillars, website content, headlines, calls to action, and persona-specific messaging. Conduct client discovery, competitive research, and stakeholder interviews; collaborate with designers, developers, strategists, and SEO specialists; edit existing copy; and ensure all deliverables are clear, accurate, differentiated, conversion-focused, and on-brand.

Lead sales for SAP Embedded Payments (MBC), engaging CFOs, treasury and IT teams to sell integrated payment and connectivity solutions. Manage full pipeline from lead generation to close, craft value propositions, collaborate with presales/solution architects, build partner relationships, and represent the company at industry events.

Provides strategic consulting support to energy and climate technology clients across business development, policy, regulatory, go-to-market, and fundraising objectives. Responsibilities include researching energy markets and regulations, managing client accounts, developing memos and presentations, engaging stakeholders, shaping policy strategies, and helping clients close deals and achieve regulatory outcomes.

Lead AI consulting growth in the energy, oil and gas sector by advising executive clients, originating and expanding enterprise engagements, shaping AI use cases, managing commercial lifecycles and P/L, and overseeing delivery. Build strategic account plans, guide cross-functional consultants and technical teams, support thought leadership, and translate operational challenges into scalable solutions such as predictive maintenance, computer vision, safety automation, document processing, and digital twin pipelines.

Manage a portfolio of B2B customers in Thailand, leading onboarding, product adoption, retention, renewals, and upsell opportunities. Build executive relationships, develop customer success plans, and collaborate with Sales, Marketing, Product, and Renewals. The role also supports business development by identifying prospects, conducting outreach, researching the Thai EdTech market, supporting localized campaigns, and tracking expansion metrics.

Lead the design, development, deployment, and operation of production AI and ML systems. Build high-throughput Python services and Databricks pipelines, support traditional ML and LLM applications, establish testing and deployment standards, and develop monitoring for quality, reliability, latency, throughput, and cost. Partner with product, research, and responsible AI teams on governance and release criteria. Provide architectural leadership, conduct code reviews, mentor engineers, and resolve complex technical dependencies.