Software Engineer

4 weeks ago

Delhi, Delhi, India Infraveo Technologies Full time

We are looking for a highly skilled and motivated Software Engineer with expertise in Graph Neural Networks (GNNs) to join our remote team. This role is ideal for someone who is passionate about open-source software, thrives in solving real-world problems through graph-based machine learning, and wants to contribute to innovative and scalable ML systems.

Key Responsibilities :

- Design, develop, and implement advanced Graph Neural Network (GNN) models for real-world applications.

- Contribute to open-source software (OSS) projects, including bug fixes, new features, and documentation.

- Build and optimize large-scale machine learning systems using Python and modern ML frameworks.

- Troubleshoot, debug, and resolve complex system and algorithmic issues in production environments.

- Collaborate with research and engineering teams to take GNN models from proof-of-concept to production.

- Automate routine tasks and model workflows to improve scalability and deployment efficiency.

- Stay up to date with the latest research and trends in GNNs, deep learning, and ML infrastructure.

Required Skills and Qualifications :

- 3+ years of experience designing and implementing machine learning algorithms, preferably with a focus on GNNs.

- At least 2 publications in top-tier ML/AI conferences such as NeurIPS, ICML, ICLR, or similar, specifically related to graph-based ML.

- Proficiency in Python and deep learning frameworks, especially PyTorch.

- Solid understanding of graph theory, message passing, node embeddings, and graph representation learning.

- Experience building or scaling large ML systems in real-world environments.

- Excellent debugging skills and the ability to diagnose complex issues across stacks.

- Strong analytical thinking, communication skills, and a high sense of ownership.

- Hands-on experience with graph ML libraries such as PyTorch Geometric, DGL, or Deep Graph Library.

- Experience with distributed training, GPU acceleration, and cloud-based ML pipelines.

- Contributions to well-known open-source repositories in ML or GNN domains.

- Familiarity with DevOps tools and MLOps workflows.

- Passionate about open-source development and real-world impact through AI.

- Self-motivated, detail-oriented, and comfortable working in a fully remote team.

- Able to balance research innovation with engineering practicality.

(ref:hirist.tech)

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