Top Remote Machine Learning Jobs in Buffalo, NY

The Senior Backend Engineer will develop and maintain backend systems, collaborate on data-driven solutions, and enhance products using machine learning.

Design and implement scalable machine learning pipelines, collaborate with cross-functional teams, ensure deployment standards, and champion best practices in observability and monitoring.

Develop and optimize machine learning models and workflows to enhance insurance processes. Collaborate on model integration, monitoring, and improvement while driving innovation in modeling techniques.

The Senior Display Media Account Manager develops and executes digital media strategies, focusing primarily on Amazon DSP, while fostering client relationships, providing analytics, and driving business growth for clients.

The Senior Product Marketing Manager will develop strategies, create messaging frameworks, and produce marketing materials to effectively communicate Socure's value in the identity verification and fraud prevention market while collaborating with cross-functional teams.

As a Senior Machine Learning Engineer, you'll design and implement ML models, develop data pipelines, and collaborate on AI features at Mural.

As a Senior Machine Learning Platform Engineer, you'll architect a scalable ML platform, collaborating with teams to ensure compliance, optimize performance, and guide best practices in ML workflows.

Design and deploy machine learning models for autonomous vehicles, focusing on data tagging, dataset curation, and model validation.

The Machine Learning Engineer will fine-tune and deploy Large Language Models, optimize ML models, maintain data pipelines, and collaborate on AI features.

The role involves building and maintaining ML pipelines, optimizing workflows, and contributing to product strategy with a focus on usability.

The Senior AI Engineer will develop AI solutions for incident management, collaborate cross-functionally, and enhance observability tools through iteration and ownership.

Design, build, and maintain ELT pipelines and analytics-ready data models to support reporting, KPIs, and downstream ML use cases; implement data quality, optimize pipeline performance, document lineage, and ensure governance and privacy.

Design and maintain datasets, build and evaluate domain-specific ML and vision-language models for real-time privileged access threat detection; deploy and optimize Python/Docker inference services integrated with WebSocket/WebRTC and protocol-level interfaces; monitor and document production models.

Lead QA for AI/ML features: design and execute test plans, build Python automation to validate LLM outputs, guardrails, and data pipelines; perform regression, security/privacy validation, and analyze logs/metrics to ensure reliability.

Design and build machine learning models for Zillow's product features, optimize AI components, and mentor engineers within a cross-functional team.

Lead data acquisition and management strategies for AI models, analyze data systems, oversee partnerships, and guide a team in optimized data usage.

Lead the definition and rollout of AI-powered product features, collaborating with teams to enhance fraud prevention solutions.

Manage a team of data scientists and analytics engineers to innovate Netflix's core product experience, driving measurement and insights across the TV and interactive discovery domains.

Lead the development of first-party measurement solutions, integrate with third-party partners, and ensure high-quality analytics outputs within the ads ecosystem.

Lead Reliability & Observability initiatives, collaborate with engineering and product teams, ensure robust operations of Airbnb's platform, and drive AI projects.

Design, build, and scale data and ML systems; collaborate cross-functionally; implement data quality and governance frameworks; document data processes.

The Senior Machine Learning Engineer will build and operate ML systems end-to-end, focusing on production-grade ML platforms, feature pipelines, and MLOps practices while collaborating with cross-functional teams.

The Machine Learning Engineer will develop and integrate ML solutions, maintain ML systems, build data pipelines, and collaborate with cross-functional teams.

Analyze biological datasets using machine learning and deep learning, collaborate on research projects, and communicate findings through visualizations and reports.

The AI/ML Specialist Solution Architect Intern will assist in designing AI solutions, learning about distributed workloads, and preparing technical materials, gaining mentorship and exposure to modern ML frameworks and GPU infrastructure.