Top Machine Learning Jobs in Buffalo, NY

Lead technical strategy and hands-on engineering for Airbnb's AI-powered ads growth engine. Architect scalable systems for creative generation, bidding, budget optimization, and audience management across paid channels. Write and review code, set standards for availability and quality, collaborate with Marketing/Product/ML teams, roll out staged automation, and mentor engineers to advance platform autonomy while ensuring brand safety and human-in-the-loop controls.

Lead and deliver complex, cross-team AI product programs, drive agent-first SDLC adoption, ensure integration and operational readiness of AI workflows, define metrics, communicate risks and status, and standardize TPM best practices across Product and Engineering.

Partner with a retained search firm to place software engineers and quant developers at top hedge funds. Provide candidate flow from your network; firm supplies clients, process, and fees. Remote, commission-only role with placement and pipeline incentives. Apply with placement examples, outreach metrics, and a candidate submission.

Serve as primary client contact for a portfolio of loyalty-program clients. Scope and manage end-to-end actuarial analyses rooted in predictive modeling and machine learning, validate model outputs, translate results into clear recommendations and presentations, and partner with analysts and data scientists to deliver high-quality, client-facing work in a fully remote consulting environment.

As an AI/ML Data Contributor, you'll perform data labeling, content evaluation, and user testing to improve machine learning models. Tasks are flexible and may include remote or in-person participation.

Lead client-facing Data & Analytics engagements across pre-sales, architecture, and delivery. Define strategy, roadmaps, solution designs, and SOWs for modern data platforms, pipelines, governance, analytics, and AI enablement. Drive practice development, create reusable IP, mentor teams, and ensure quality delivery and strong business outcomes.

As a Senior Technical Product Manager, you will lead the AI Platform team to define roadmaps, collaborate with technical experts, and improve healthcare delivery by leveraging AI technologies.

Lead and execute product strategy for Everyday Money: define product thesis and roadmap, ship product lines, run AI innovation lab for agentic consumer experiences, manage and develop PMs, partner with design, Credit, and external partners, and own business economics and compliance for durable retention and monetization.

Provide transactional counsel on open source licensing/compliance, AI-related licensing, and IP licensing. Review external publications and developer-facing materials, negotiate university research and data agreements, draft IP terms in commercial agreements, build playbooks/templates, and partner with engineering, data science, marketing, and international colleagues to manage IP risk and govern open source releases.

Lead and deliver complex, cross-team AI platform programs: manage schedules, risks, integration of AI workflows and agents, enable operational readiness, drive TPM best practices, and communicate status and metrics to stakeholders in a remote, multi-timezone environment.

Own RevOps data models and BI infrastructure to drive GTM strategy. Clean and analyze datasets, build predictive models, define and track leading/lagging KPIs, deploy dashboards, document data definitions, and deliver executive-ready insights while partnering cross-functionally with Finance and GTM teams.

Lead go-to-market strategy for Magnet Forensics' security, incident response, and AI product portfolio. Influence executive, product, and sales stakeholders; translate technical AI/ML and forensic capabilities into messaging; develop buyer personas; create sales enablement and demand-generation content; evangelize products at events; partner with competitive intelligence and customer advocacy; mentor product marketing team members.

Lead enterprise design and deployment of standardized, scalable bovine IVF production systems. Drive process architecture, SPC, automation, AI/advanced analytics, Lean/Six Sigma, quality systems, and organizational development to reduce variability, increase throughput, and ensure consistent outcomes across laboratories and field operations.

Drive independent, high-impact research on frontier AI topics, publish findings, collaborate widely, and mentor new researchers in the field.

Lead client-facing full-stack Java development, mentor teams, design solutions, promote engineering best practices (Agile, DevOps, CI/CD, TDD), and deliver enterprise software using modern cloud, container, and JS frameworks.

Lead the commercial engine: build partnership function, close enterprise platform partnerships, own full marketing (positioning, content, paid, website), design AI-leveraged GTM stack, translate product-market fit, run pipeline and commercial reporting, and hire a team when metrics justify growth.

Lead procurement strategy and supplier selection for inbound products and services. Manage RFIs/RFPs, negotiate contracts with Legal, administer Coupa purchase orders, reconcile invoices, and apply AI/ML and reporting tools to optimize procurement processes while collaborating with cross-functional senior stakeholders.

Lead enterprise design and deployment of a global operating model for bovine IVF production. Drive standardization, SPC, automation, AI/analytics, Lean/Six Sigma, quality systems, and continuous improvement to scale consistent, high-throughput production across labs and field operations.

The Director of System Safety oversees safety functions for autonomous vehicles, managing safety cases, deployment plans, and regulatory relationships while leading a multi-disciplinary safety team.

The Software Engineering Manager will lead a team in creating tools for Cengage Learning Platforms, focusing on AI innovation, team growth, agile delivery, and collaboration.

Own a product area of the Content Authoring Platform end-to-end: set vision and roadmap, run continuous discovery, define and measure outcomes, partner with engineering and design to deliver features, evaluate and apply AI capabilities prudently, mentor peers, and communicate strategy and trade-offs to stakeholders.

Lead discovery, definition, and delivery of B2B SaaS product features. Own customer research, data-driven prioritization, UX collaboration, KPI tracking, and cross-functional execution with engineering, marketing, and customer success.

Lead development of time-series and econometric models (ARIMA, VAR, state-space, WLS, panel data) and Bayesian probabilistic frameworks. Use causal inference and stochastic processes to produce actionable insights, work with large datasets on Databricks, communicate results to stakeholders, and mentor junior team members.

Lead and coordinate end-to-end fraud risk engagements, structure analytical solutions, guide analytics teams, communicate with clients and senior stakeholders, manage timelines, build fraud rules/governance, and identify additional client opportunities.

Senior Business Systems Analyst to define requirements for agent-facing servicing applications, design integrations/APIs with core banking systems, translate needs into user stories and acceptance criteria, improve agent workflows and productivity, and identify AI/ML opportunities for fraud detection, automation, and operational analytics. Supports testing, validation, and releases.