Machine Learning Jobs in Jersey City, NJ

Lead cybersecurity architecture for enterprise applications and platforms: evaluate principles and controls, design cloud-native secure solutions, provide technical guidance, influence stakeholders, apply threat modeling and frameworks, and build reusable security patterns and guardrails to improve security outcomes.

The Director of Developer Relations leads the strategy for engaging developers around CoreWeave's AI SaaS offerings, creating content, fostering community, and improving the onboarding experience.

Lead design and adoption of cloud-based, portable AI platform architectures across hybrid environments. Advise on technology selection, document target-state designs, shepherd architecture reviews, develop multi-year roadmaps, integrate enterprise AI capabilities, produce secure production code, and align engineering with architectural governance and controls.

Lead Data Architect responsible for defining and evolving data architecture and standards across 100+ applications, driving adoption of strategic data lake platforms, designing target-state architectures and data exchange patterns, mentoring junior architects, and ensuring governance, data quality, and cloud-based database best practices.

The Senior Product Marketing Manager will position CoreWeave's SUNK offering, develop messaging, and collaborate with engineering and sales teams to enhance product adoption and market understanding for AI training workloads.

Lead a software engineering team to design, build, and maintain secure, resilient Java-based applications. Develop and review production-quality code, drive adoption of AI-assisted engineering practices, automate remediation and SDLC tooling, evaluate vendor solutions, and coach engineers on secure and responsible AI use. Promote reuse, operational stability, and agile/CI-CD practices within financial services applications and cloud-native environments.

Design, develop, test, and maintain secure, high-quality production software. Create architecture and design artifacts, analyze large datasets to improve systems, troubleshoot complex problems, and contribute to engineering communities and inclusive team culture.

Lead architecture design and governance for trade surveillance products, provide technical direction, integrate enterprise AI securely and auditable into architectures, develop and review production code, and establish reusable SDLC/toolchain patterns.

Lead design and deliver reusable, cloud-native components and SDKs; write and review secure production code; automate remediation and CI/CD; drive adoption through communities of practice; evaluate vendor and internal architectures, and improve operational stability across the enterprise.

Provide commercial legal support for enterprise cloud, SaaS, and infrastructure transactions. Draft, negotiate, and advise on contracts (SaaS, IaaS, software licensing, DPA), counsel sales and cross-functional teams on legal/privacy/commercial risk, manage concurrent deals, improve templates and processes, and coordinate outside counsel to enable scalable, business-focused legal support for growth.

Lead design, develop, and deploy secure, scalable full-stack applications (Java or Python) for finance planning and analysis. Drive architecture reviews, operational stability, CI/CD automation, cloud-native AWS deployments, and integration of AI/ML/LLM capabilities. Mentor teams and lead engineering communities of practice.

Lead site reliability for liquidity risk applications, owning non-functional requirements. Drive resiliency, security, scalability, monitoring, automation, and enterprise-authorized AI adoption for reliability workflows. Influence strategy, run blameless post-mortems, coach engineers, hire and develop talent, and ensure traceability, auditability, and cross-team collaboration.

Lead AI engineering teams to design, build, and deploy end-to-end AI solutions. Manage client relationships, plan and deliver projects, mentor staff, drive adoption of cloud-native microservices, CI/CD, vector databases and orchestration tools, and ensure high standards of quality, innovation, and compliance.

Lead teams applying advanced data science and machine learning to large-scale claims, clinical, and member data to generate actionable insights that reduce cost of care and improve population health. Manage client relationships, mentor staff, ensure project delivery and quality, develop payer-focused analytics products, present findings to senior stakeholders, and promote continuous improvement and knowledge sharing.

Lead design, build, and operate cloud-native AI/ML platform infrastructure and shared services. Architect scalable, secure GPU-enabled training and inference environments, implement IaC and automation, support model deployment/serving pipelines, drive observability and CI/CD, and promote responsible AI practices and enterprise AI-assisted development across teams.

Lead architecture and delivery of production-grade agentic AI and NLP solutions for client onboarding. Design reusable frameworks (RAG, multi-agent orchestration, LLMs), integrate agents into enterprise systems, define safety/guardrails, advise stakeholders, and champion AI-assisted SDLC improvements to improve delivery, quality, and operational outcomes.

Lead design and implement scalable, secure ML and LLM-powered solutions on cloud. Produce production-quality Python code, build data pipelines and model inference services, drive AI governance and SDLC best practices, mentor teams, and collaborate cross-functionally to operationalize GenAI capabilities.

Lead cybersecurity architecture for cloud-native enterprise solutions: evaluate controls and new technologies, advise stakeholders, provide technical guidance, promote firmwide SDLC practices, and mentor peers to mitigate risk and adopt strategic solutions.

Lead development of secure, high-quality production software for analytics and credit risk; design, code (Python/Java), review, troubleshoot, automate remediation, drive CI/CD and cloud-native solutions, mentor junior engineers, evaluate vendors, and promote new technologies.

Design and deliver architecture solutions for Markets technology products, produce architecture and design artifacts, write secure production code, apply enterprise-authorized AI across SDLC, lead technology evaluations, ensure resiliency/security/operational readiness, and contribute to architecture governance and communities of practice.

Design and implement enterprise cybersecurity architecture for cloud-native applications. Embed security across SDLC and CI/CD, build Python automation for monitoring and remediation, evaluate vendors, lead practice communities, and collaborate with risk and compliance to translate regulatory requirements into technical controls while validating AI-assisted security outputs.

Lead technical delivery for analytics-focused software: design, develop, test, and operate secure, high-quality production code. Drive automation and CI/CD, evaluate vendor/architecture choices, mentor junior engineers, and promote resilient cloud-native solutions within financial services technology teams.

Lead and contribute to an agile engineering team building scalable, secure big-data applications. Provide technical guidance, design and produce production-quality code, drive architecture and tooling decisions, champion AI-assisted engineering practices, and collaborate across global teams to ensure operational stability and delivery.

Design, build, and scale production-grade NLP and LLM-based solutions (search, summarization, classification, recommendations). Own end-to-end model lifecycle, partner with product/engineering/operations/risk, improve data quality and feedback loops, monitor models in production, and optimize workflows to reduce agent effort and improve consistency.

Build and validate ML, optimization, and statistical models on large structured and unstructured consumer datasets; generate insights and actionable recommendations; communicate results to senior stakeholders; contribute across the full modeling lifecycle and advance team knowledge.