Top Machine Learning Jobs in San Diego, CA

As a Machine Learning Engineer specializing in natural language processing at Entefy, you will use deep learning and various methodologies to develop innovative algorithms that enhance communication technologies. Your responsibilities will include working on confidential high-impact projects and applying your knowledge in machine learning theory and text analytics.

The Staff ML Engineer / ML Team Lead at Zencoder will lead the development of AI-driven solutions, focusing on AI pipelines and models for code generation and refinement. Responsibilities include creating embedded AI agents, collaborating with teams, testing solutions, and staying updated on industry trends.

As a Senior Software Engineer at Zencoder, you will develop AI-driven solutions for code generation and assistance tools. You'll utilize your programming skills in Python, Java/Kotlin, or TypeScript to enhance code generation and repair. Collaborate on projects involving VSCode and JetBrains plugins, ensure code efficiency, and stay updated with industry trends.

The Sr. Manager of ML Production Engineering leads the ML Production Engineering function, managing the engineering team responsible for Matterport’s 3D reconstruction pipeline. It involves optimizing ML Ops and Dev Ops, collaborating on designing and implementing ML pipelines, and overseeing the integration of ML models into applications.

The Lead AI/ML Engineer will build, deploy, and manage machine learning models to tackle complex data challenges within the location data domain. Responsibilities include enhancing data accuracy, developing ML pipelines, utilizing NLP for multilingual data, and collaborating with cross-functional teams to innovate and improve data processing methods.

As an ML Platform Engineer, you will develop APIs and systems to enhance the deployment and serving of machine learning models. Your role includes building scalable services and frameworks while collaborating with data scientists to improve ML infrastructure and operations.

As a Staff Machine Learning Engineer, you will design and develop scalable ML platforms and services, define and maintain Machine Learning data pipelines, productionize models, optimize performance, automate workflows, and promote best software engineering practices. You'll collaborate with cross-functional teams to drive ML roadmap and architectural decisions while improving productivity through shared tools.

The Senior Manager of ML Platform at Stitch Fix will lead a team to build and enhance systems for deploying machine learning models, mentor engineers, and collaborate with various stakeholders on challenges in distributed systems.

As a Software (ML Product) Engineer, you will enhance the user experience of ML tools by optimizing workflows and processes. You will collaborate with technical product managers, contribute to defining efficient ML practices, and improve DVC, an open-source tool for machine learning. A strong background in deep learning and system design is necessary to transform current workflows and engage with the ML community.

As a Lead AI ML Engineer, you will design, develop, and deploy machine learning models and data pipelines, drive impactful business decisions, and manage the data infrastructure in collaboration with data engineers and scientists while ensuring high-quality outputs.

As a Senior Software Engineer II in ML Core, you'll define backend architecture and implement changes for scalable products at Splice. You'll optimize the search infrastructure, manage ML model production, advocate for system design, and mentor junior engineers while contributing to team improvement and customer-centered solutions.

The Senior Software Engineer will design, build, and maintain scalable machine learning systems, collaborating closely with engineers and researchers. Responsibilities include deploying ML models, managing cloud services, and developing infrastructure for rapid ML development.

As a Senior AI/ML Engineer, you will design, train, and deploy machine learning models, collaborate with cross-functional teams, and maintain machine learning pipelines. You will utilize tools such as PyTorch, Kubernetes, and Apache Spark, and will need a strong understanding of various machine learning subfields with a focus on NLP, CV, and Time Series.

The Machine Learning Engineer will enhance the scalability and efficiency of data science solutions, operationalize AI/ML algorithms, and build automated systems for model training and monitoring, collaborating closely with data scientists and product teams.

As a Senior AI/ML Engineer at WEX, you will design, implement, and maintain machine learning algorithms and systems, collaborate with engineering teams to integrate AI models, manage version control and implement CI/CD pipelines, and communicate complex solutions to varied stakeholders.

The Principal ML Engineer will lead the machine learning platform engineering team, providing hands-on technical leadership, mentorship, and code reviews. They will ensure operational excellence by delivering superior infrastructure, collaborating with product managers and data scientists, and guiding innovation in AI/ML technologies.

The Senior AI/ML Engineer will develop and optimize AI-powered systems, analyze member behavior through data, and improve ML models for better health outcomes. Collaboration across teams is essential to design AI-powered experiences. The role necessitates expertise in AI and ML systems, particularly in reinforcement learning and deep learning techniques.