Top Machine Learning Jobs in Philadelphia, PA

The Senior AI/ML Engineer will design and maintain scalable ML infrastructure, mentor data scientists, and ensure production readiness of AI models.

Lead the development of AI agents and infrastructure, collaborate with stakeholders, design APIs and SDKs, and advocate for best practices.

The Solutions Architect for AI/ML at Snowflake will advise clients on best practices for Data Science workloads, design solutions, and build ML pipelines. Responsibilities also include working hands-on with SQL and Python, maintaining technical expertise and collaborating with teams to improve products.

The Senior Software Engineer will develop and maintain foundational ML infrastructure for feature computing, storage, and retrieval, impacting numerous teams at Reddit.

The Practice Manager leads Data Science, AI, and ML projects, managing teams, fostering growth, and ensuring customer success through technical guidance and strategic business planning.

The Senior Machine Learning Engineer will develop scalable ML systems, lead a team, mentor juniors, and work cross-functionally to enhance customer experience through machine learning solutions.

The engineer will build end-to-end applications, analyze data trends, deploy solutions, and improve process efficiency for the solar industry.

The Senior Product Manager will lead the strategy and execution of AI-driven features in a SaaS platform, ensuring high-quality user experiences and data-driven decisions while mentoring junior team members.

As an ML Engineer, you will build and deploy machine learning models for autonomous robots, collaborating with ML scientists and engineers to enhance AI capabilities.

Lead ML projects to optimize search and recommendations at Airbnb, collaborating with cross-functional teams to enhance user experience and business impact.

Lead the design, development, and implementation of machine learning products, creating data pipelines and maintaining production stability.

The Staff Machine Learning Engineer will design and deploy ML models, build real-time model APIs, and collaborate across teams to drive user growth and revenue through AI/ML solutions.

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

As a Staff ML Engineer, you will develop and deploy machine translation models, collaborating across teams to enhance Airbnb's translation capabilities and improve global guest experiences.

The role involves developing scalable ML solutions, leading cross-functional discussions, analyzing knowledge data, and producing technical documentation to improve search relevance using AI and machine learning technologies.

Develop and deploy ML models for personalization and optimization, analyze performance, and collaborate with product teams to enhance user experiences.

Design, develop, and deploy machine learning systems, improve ML infrastructure, and partner with stakeholders to enhance data science workflows.

The role involves building scalable AI features, optimizing machine-learning pipelines, evaluating LLM outputs, and ensuring compliance with data governance standards.

As a Machine Learning Engineer, you'll build scalable ML systems for personalized recommendations, collaborating with data scientists and cross-functional partners.

The Senior Machine Learning Engineer will develop ML platforms, optimize model lifecycles, lead initiatives, and maintain code quality, collaborating with Data Science teams.

Lead the development of advanced recommendation systems and ML pipelines. Collaborate with cross-functional teams to enhance user engagement through optimization of machine learning models at scale.

Lead the design and development of AI solutions, optimize algorithms, collaborate with teams, and develop advanced models to drive business insights.

The role involves developing and optimizing intelligent agents using large language models, collaborating with the team, and solving technical problems.

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

Lead technical strategy and architecture for AI projects, manage client engagements, mentor engineers, and drive innovation in machine learning solutions.