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The Software Engineer will focus on developing infrastructure solutions for AI/ML applications. Responsibilities include optimizing performance, collaborating with teams to enhance infrastructure management, and researching machine learning systems. The role requires expertise in distributed systems and proficiency in multiple programming languages.

Systems Research Engineer specialized in GPU Programming, responsible for developing and optimizing GPU-accelerated kernels and algorithms for ML/AI applications. Co-design GPU kernels and model architecture to enhance performance and efficiency of AI systems. Contribute to co-design of efficient GPU architectures and programming models. Stay up-to-date with latest advancements in GPU programming techniques.

The Machine Learning Engineer will optimize AI inference systems, develop runtime inference services, and collaborate with teams to enhance AI capabilities. Responsibilities include designing production systems, conducting code reviews, and implementing robust data processing systems.

As an ML Engineer at Together AI, you will develop a platform for customizing open-source models, collaborate with product and research teams, ensure API reliability, and contribute to the open-source AI ecosystem. Key responsibilities include building systems, creating tooling, ensuring stability, analyzing methods, and developing new features. Ideal candidates have 2+ years of ML deployment experience, knowledge of fine-tuning methods, strong Python or Go skills, and a passion for reliable tools. Standout experiences include large-scale system development, advanced fine-tuning methods, open-source contribution, and ML workload management on Kubernetes.

Research and build the next generation AI platform at Together AI, design large-scale distributed training systems and low-latency/high-throughput inference engine, stay up-to-date with latest advancements in machine learning systems.

Senior Cloud Engineer responsible for building a highly available, global, multi-cloud PaaS platform for AI workloads. Must have experience with infrastructure-as-code, cloud microservices architectures, Kubernetes, and software development fundamentals.

Senior DevOps Engineer responsible for developing and optimizing cloud infrastructure for AI workloads on distributed GPU hardware. Requires 5+ years of DevOps experience, proficiency in programming languages, and expertise in CI/CD, cloud computing, and Kubernetes.