Machine Learning Research Intern

Machine Learning Research Intern 

At Convergence, we're transforming the way AI integrates into our daily lives. Our team is developing the next generation of AI agents that don't just process information but take actions, learn from experience, and collaborate with humans. Proxy is the latest advancement in personalised AI assistants, using Parallel agents and our DeepWork Model to save users thousands of hours of time. Users are able to craft their own automations, share them in our template hub, or use community creations.

With a recent $12 million pre-seed funding from Balderton Capital, Salesforce Ventures, and Shopify Ventures, we're poised to make a significant impact in the AI space. Join us in shaping the future of human-AI collaboration and be part of our mission to transform the AI landscape.

We are looking for talented machine learning research interns to join our team and focus on training models or agentic workflows which power Proxy, our generalist agent.

You will work with a small team — equipped with lots of GPUs – to train models, including multi-modal vision LLMs and action models.

• Develop novel state-of-the-art algorithms and corresponding systems, leveraging various deep learning techniques

• Analyze and improve various aspects of the corresponding algorithms and systems, including efficiency, scalability, stability, fairness, security, and privacy

• Perform state of the art research to advance the science and technology of Machine Learning and Artificial Intelligence

• Collaborate with researchers and cross-functional partners including communicating research plans, progress, and results

• Publish research results and contribute to research that can be applied to Convergence product development

• Research experiences with LLM Agents

• Currently has or is in the process of obtaining a Ph.D. degree in Computer Science, Machine Learning, Artificial Intelligence, or relevant technical field

• Must obtain work authorization in country of employment at the time of hire and maintain ongoing work authorization during employment

• Familiar with reinforcement learning

• Experience with Python, C++, C, Java or other related languages

• Experience with deep learning frameworks such as PyTorch or Tensorflow

• Intent to return to degree program after the completion of the internship/co-op

• Proven track record of achieving significant results as demonstrated by grants, fellowships, patents, as well as publications at leading workshops or conferences such as NeurIPS, ICLR, AAAI, ICML, KDD, IJCAI, CVPR, ECCV, ACL, NAACL, or similar

• Demonstrated experience and self-driven motivation in solving analytical problems using quantitative approaches

• Direct experience training LLMs or VLMs with methods such as distillation, supervised fine-tuning, and policy optimisation

• Experience training Llama models or other open source models

• Experience with frameworks for fine-tuning and RLHF

• Be at the cutting edge of AI and foundation models

• Work on challenging problems that impact users' daily lives

• Collaborative and innovative work environment

• Opportunities for professional growth and learning

• Competitive salary and benefits package