Machine Learning / Research Engineer (New Grad)
About Together AI Together AI is a research-driven AI company. We believe open and transparent AI systems will drive innovation and create the best outcomes for society, and together we are on a mission to lower the cost of modern AI systems by co-designing software, hardware, algorithms, and models. We have contributed to leading open-source research, models, and datasets to advance the frontier of AI, and our team has been behind technological advancement such as FlashAttention, Hyena, FlexGen, and RedPajama. We invite you to join a passionate group of researchers and engineers in our journey in building the next generation AI infrastructure. Role Overview As a Machine Learning/Research Engineer (New Grad), you’ll contribute to cutting-edge AI research and development, working on projects that range from training large-scale models to exploring novel algorithms. You’ll collaborate with researchers and engineers to push the boundaries of machine learning, with a focus on reliability and performance. This role is perfect for recent graduates passionate about AI, eager to blend research exploration with practical engineering. Responsibilities • Implement and optimize machine learning models and algorithms
- Collaborate with researchers to design, run, and analyze experiments using frameworks like PyTorch or TensorFlow.
- Build and maintain infrastructure for training and evaluating AI models
- Contribute to research discussions, proposing ideas to advance our understanding of AI systems.
- Write clean, well-documented code and participate in code reviews.
- Stay updated on the latest advancements in machine learning and AI safety.
- Strong programming skills in Python and familiarity with ML frameworks
- Deep understanding of machine learning concepts (e.g., supervised/unsupervised learning, neural networks, reinforcement learning).
- Experience with data structures, algorithms, and software engineering principles.
- Ability to balance research exploration with practical implementation and communicate findings clearly.
- Passion for AI research and its societal impact.
- Bonus: Contributions to open-source ML projects, research papers, or experience with large-scale distributed systems.
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