Top Machine Learning Jobs in Buffalo, NY

The role requires a skilled Machine Learning Engineer to create complex models and AI solutions while collaborating with teams to enhance products and services.

As a Data Scientist/Machine Learning Engineer, you'll finetune models, improve data quality, add new signals, and push solutions to production.

As a Product Manager, you'll transform data into opportunities, manage technical product development, and foster cross-functional collaboration for philanthropic initiatives.

Develop and optimize unimodal and multimodal perception models for 3D/BEV terrain and surface inference, build large-scale data pipelines and annotation tools, deploy and optimize models on edge compute, collaborate with robotics/software/hardware teams, mentor juniors, and translate research into production-grade autonomous vehicle perception systems.

As a Machine Learning Engineer, you will design and build AI capabilities, develop scalable ML infrastructure, and collaborate on production systems in the real estate domain.

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 develop AI products, support feature implementation, and troubleshoot ML services to enhance customer experiences.

The role involves applying AI/ML techniques to develop model systems for healthcare, collaborating across teams, and conducting R&D.

The VP of Research, Machine Learning will set research direction for AI systems, focusing on context representation, reasoning, and evaluation frameworks while ensuring product safety and alignment.

Responsible for building and maintaining end-to-end ML pipelines and deploying production-grade ML systems. Tasks include model fine-tuning, evaluation, and collaboration with engineering teams.

As an AI/ML Data Engineer, you will design and build data and ML infrastructure to create personalized student experiences, working on ETL processes, feature stores, and collaborating with product and data science teams.

Lead computer vision projects and develop ML models for power grid analysis while mentoring engineers and ensuring software quality standards.

The Senior Machine Learning Operations Engineer will design, build, and maintain ML infrastructure, streamline model deployment, and monitor performance to ensure the success of machine learning models at The Athletic.

The Senior ML Engineer will automate component placement on PCBs, working on R&D and production using ML and optimization techniques.

As a Senior/Staff ML Systems Engineer at Quilter, you'll design and maintain ML infrastructure for automated PCB component placement, manage data pipelines, and lead systems design reviews while ensuring project efficiency and reliability within a fully distributed team.

As a Senior Machine Learning Engineer, you'll design and develop infrastructure and models for AI-powered applications while collaborating with teams to enhance product functionality.

As a Staff Machine Learning Engineer, you will design and evaluate ML models, optimize performance, and work with stakeholders to deliver AI solutions.

As a Senior Machine Learning Engineer, develop LLM evaluation frameworks and agentic AI workflows to extract insights from conversations and optimize customer experiences.

Develop, evaluate, and deploy AI systems and machine learning models, focusing on NLP and multimodal models. Collaborate with teams and publish research.

This role involves deploying and optimizing machine learning models for autonomous vehicle motion planning, ensuring performance and reliability in production settings.

Lead a team to develop large-scale data analysis frameworks and ML models for autonomous vehicles, driving project execution and innovation.

Lead the development of device intelligence and fingerprinting systems by designing backend services, collaborating on integrations, and applying advanced machine learning algorithms to enhance security and combat fraud.

Seeking Applied Scientist to build scalable AI systems for estate planning, focusing on production-grade applications and document understanding using advanced AI models.

The Lead AI/ML Engineer evaluates emerging technologies, leads teams in adopting solutions, and provides technical leadership while mentoring junior specialists.

Lead technical direction for AI across products, architect RAG services, mentor engineers, and ensure compliance in AI usage.