Top Software Engineer Jobs

The Principal Generative AI Engineer will lead the development and implementation of the Generative AI roadmap at Madrigal Pharmaceuticals, focusing on creating business-facing experiences with LLMs, providing technical leadership, solution architecture, and fostering collaboration with cross-functional teams while ensuring the optimization and fine-tuning of AI technologies.

The AI/ML Engineer will develop Generative and Traditional AI platform capabilities on enterprise and cloud platforms. Responsibilities include delivering AI models to infrastructure, optimizing scoring pipelines, automating model deployment, collaborating with teams for end-to-end model delivery, and providing guidance on software engineering principles. Additional support for production issues is expected.

As an AI Scientist at WorldQuant, you will conduct research in Machine Learning to enhance investment processes, produce predictive signals, design deep learning architectures, and collaborate with investment professionals to optimize algorithms.

The Senior Artificial Intelligence Developer will collaborate with product management, designers, and engineers to enhance app development through data insights and experimentation. Responsibilities include exploring user behavior data, measuring user engagement, building data products, and presenting findings to stakeholders.

The role involves developing processes to generate written content from transcripts or audio files using tools like OpenAI and GPT-3. It also requires editing audio and video files. The position starts part-time and may evolve into a full-time role, emphasizing self-direction and detail orientation.

The role involves collaborating with hardware and software engineers to optimize AI/ML workloads, troubleshoot issues, analyze performance bottlenecks, and contribute to innovative hardware solutions. Candidates will research ML trends and develop scalable systems to enhance performance and efficiency.

The Senior Staff, AI/ML Platform Architect will be responsible for defining the platform architecture for AI/ML compute in data center applications, managing the technology roadmap, and leading discussions with stakeholders to enhance performance, power, and cost efficiencies in silicon products.

The AI Solution Manager will lead teams in delivering AI/ML applications, collaborate with federal agencies to identify use cases, and convert project experiences into product strategies. This role requires regular travel and a focus on developing solutions for complex problems in the intelligence community.

The ML/AI Developer will manage customer relationships and oversee the deployment of machine learning solutions in various applications, collaborating with team members on software development, system design, and optimizations to deliver robust AI solutions.

The Head of Applied AI will lead the execution of AI projects, collaborating with leadership and cross-functional teams to drive successful outcomes. This role requires designing and building scalable AI systems on AWS, mentoring engineering teams, and staying updated on AI advancements while communicating complex topics effectively.

The Tech Lead Manager will oversee the fullstack product and infrastructure development for Glean's Generative AI products while providing technical leadership, coaching engineers, and fostering an inclusive team culture. They will collaborate closely with product management, design, and data science to enhance capabilities and performance.

The Staff Machine Learning Engineer will design, train, and deploy large deep learning models using data from millions of vehicles to enhance autonomous driving capabilities. This role includes establishing advanced ML infrastructure and improving model training/inference processes.

Design, train, and deploy large deep learning models utilizing vast amounts of data from a fleet of vehicles, working alongside engineers and scientists to advance autonomous driving solutions.

The Machine Learning Engineer will fine-tune and maintain large language models for Humanoid Robots and Autonomous Driving Cars, develop training and deployment pipelines, leverage large-scale datasets, explore synthetic data generation, and collaborate with teams to align on product needs.

The Senior Staff Machine Learning Engineer will design, train, and deploy large deep learning models to enhance autonomous driving capabilities. This role involves establishing ML infrastructure for large model training and inference, and requires collaboration with software engineers and research scientists to advance state-of-art machine learning models.

As an AI Performance Engineer, you will optimize the training and inference performance of machine learning models for autonomous driving, working closely with software engineers and researchers to enhance the capabilities of deep learning on NVIDIA GPU systems and AV onboard systems.

The Machine Learning Engineer will design, train, and deploy large deep learning models utilizing extensive data from a fleet of vehicles, focusing on enhancing model training and inference for autonomous driving solutions.