Top Software Engineer Jobs

As a Hardcore Engineer, you will build distributed systems for training large AI models, develop environments for agents, and optimize frameworks for data processing and inference. You will collaborate on complex engineering tasks and enhance AI model capabilities.

As a Principal Engineer in the ML/AI Platform team, you will design and maintain scalable machine learning platforms, develop reusable frameworks for model deployment, advocate for advanced technologies, and mentor team members while enhancing operational efficiency.

The Applied AI Finetuning Engineer will develop tailored LLM solutions for clients, collaborating with various teams to integrate AI into their products, execute finetuning projects, and serve as a technical advisor on best practices for deployment.

The Manager of AI and Data Engineering will lead a team of data engineers and scientists, build real-time data pipelines, and apply advanced technologies for AI research. Responsibilities include partnering with teams to ensure quality data management and advising leadership on data strategies, while also driving innovation and best practices in AI.

As a Senior Manager, Network Systems Engineer at Arista, you'll lead a team, act as a trusted advisor to customers for solutions in network architecture, and collaborate with account managers on technical proposals and product presentations. You'll focus on leveraging cutting-edge technologies in a hands-on capacity with customers, primarily onsite in Seattle.

The Network Systems Engineer will provide pre-sales technical support to clients, partnering with account managers to address requirements and opportunities. Responsibilities include conducting network architecture reviews, presenting Arista solutions, designing network proposals utilizing leaf-spine architectures, conducting proof-of-concept tests, and developing design guidelines for customer networks.

The AI Software Developer is responsible for researching, designing, and building AI/ML solutions. Key tasks include developing applications and APIs, integrating AI/ML technologies, and collaborating with teams to identify integration opportunities while improving AI/ML model functionality.

As a Senior Solutions Architect, you will lead proposal and technical teams in developing innovative solutions for government bids, ensuring compliance with RFP requirements. You'll manage the entire capture process, contribute to proposal materials, and guide clients in defining their technology needs while leveraging your extensive experience in system design and architecture.

The AI Solution Lead/Architect will design and implement AI frameworks utilizing Azure technologies, lead AI projects ensuring quality and cost-effectiveness, collaborate with data professionals, develop machine learning solutions, and provide technical expertise in AI model integration and deployment across IT systems.

As an AI for Code Research Scientist, you will improve models and research for real-world problems by prototyping concepts and running experiments, collaborating with a team to drive foundational research direction.

As an AI Research Scientist focusing on engineering and operations, you will bridge theoretical research and practical implementation of AI technologies. Your work will involve developing machine learning models, managing server infrastructure, writing code for AI applications, and collaborating with cross-functional teams to generate actionable insights from complex data sets.

The Data Engineer will be responsible for building data pipelines and infrastructure for ML models, analyzing data processing requirements, troubleshooting production issues, and collaborating with different teams at Stanford Health Care. Preferred skills include knowledge of multiple programming languages, resource management, and a collaborative mindset.

The Data Scientist will develop and implement AI and ML models to improve patient care and administrative services. They will collaborate with clinicians and researchers, evaluate healthcare data tools, and ensure the safe application of machine learning algorithms in clinical settings.

The Technical Lead II in the Operations Hub focuses on leveraging data-driven AI products to enhance customer experience. This role involves leading a small engineering team, collaborating with various departments, and fostering technical innovation. The lead will ensure product reliability and support team growth while maintaining a customer-centric approach.

The Ops Tech AI & Automation Principal Engineer will ensure quality standards for AI systems, involve rigorous testing and debugging, research and implement new technologies, focus on Generative AI development, and lead engineering activities while collaborating with a diverse team.

As a Full-Stack Monitoring & AIOps Engineer, you will manage expectations between HPE and ANL regarding responsibilities, diagnose HPC fabric issues, develop integrated software algorithms for data analysis and monitoring, leverage machine learning for performance improvements, and document installation procedures and performance metrics.

Design and build the next generation of the world's best investment management technology platform, integrate new AI services across the platform, collaborate with product engineering teams to implement AI/ML-based solutions, apply quality software engineering practices, optimize software delivery, and work in a multi-office environment.