Top Machine Learning Jobs in Buffalo, NY

The Partner Sales role involves managing partnerships to drive revenue, developing strategic partner plans, and collaborating across teams to achieve sales targets.

The Sales Engineer will drive revenue by crafting cloud data security solutions, managing demos, and consulting with stakeholders while utilizing Cyera's technology.

Develop core AI features for an AI-native product, including building LLM features, developing benchmarks, and overseeing the full lifecycle of development.

As a Research Scientist at Netflix, you will collaborate on machine learning projects to enhance content metadata and discovery, while operationalizing models.

This role involves designing AI agents, building robust infrastructure, and translating customer insights into technical requirements while working with reinforcement learning and applied data.

As a Senior Software Engineer, you'll lead software development, solve complex problems, and collaborate closely with clients to deliver business value using modern technologies.

Design and build production-grade AI systems, combining ML and LLMs, ensuring performance and reliability while providing technical leadership and mentorship.

The Director of Sales will lead enterprise infrastructure sales in healthcare, nurturing high-value prospects, and achieving revenue targets through strategic partnerships.

The Data Science Actuary role involves building and maintaining rating systems and risk models, conducting analysis for underwriting and operations, and integrating new data sources while collaborating with multiple teams.

The apprenticeship offers hands-on experience in AI/ML and software development, alongside participating in a bootcamp, working on production-level projects, and receiving mentorship.

The Principal AI/ML Architect will lead client engagements, manage engineering teams, and design scalable AI solutions while driving innovation and overseeing project lifecycles.

The ML Engineer will leverage deep learning for natural language processing tasks, impacting Entefy's products while requiring strong machine learning fundamentals and NLP expertise.

The Staff Machine Learning Engineer will develop and maintain MLOps tools, optimize model performance, and collaborate on ML system architecture with a focus on enhancing developer experience.

The role involves improving machine learning ranking models, implementing algorithms, and taking full ownership of machine learning systems within Quora's product.

Develop and tune ML models, productionize and deploy strategies for ML systems, and align cross-functionally to communicate performance metrics.

As a Staff Machine Learning Engineer, you will develop, productionize, and deploy ML models for clinical use, ensuring real-world effectiveness through hands-on coding and infrastructure building.

The Machine Learning DevRel Engineer will engage with the FiftyOne community, create documentation, code integrations, deliver courses, and provide technical support.

Assist in developing machine learning models and frameworks for ASO therapeutics, focusing on predictive models and computational strategies in drug development.

Develop machine learning models to predict molecular properties, create novel algorithms for new molecules, and collaborate with chemists and engineers to optimize performance and integrate models into software.

Lead the development of advanced machine learning models and systems, architect scalable solutions, mentor engineers, and drive improvement initiatives for product performance and innovation.

The Senior ML Engineer will design evaluations for AI features, optimize pipelines, and ensure quality in ML systems while collaborating with cross-functional teams.

Design and implement evaluation frameworks for AI systems, focusing on human+AI collaboration. Lead statistical analysis and benchmarking efforts, working cross-functionally to enhance AI model performance.

Design and deliver customer experience solutions using machine learning techniques, analyze customer data, implement ML algorithms, and automate processes.

Implement and optimize production-ready analytics code, maintain Python repositories, research data sources, build predictive models, and collaborate with teams.

Lead a team of ML Engineers to develop technology for healthcare, emphasizing hiring talent, technical leadership, and collaboration with stakeholders.