Website:
novyte.ai
Job details:
Company Description Novyte Materials focuses on applying artificial intelligence to accelerate materials discovery and optimization, bridging advanced computation with real-world materials science. The organization develops AI-driven models and tools that help identify novel materials, predict their properties, and improve performance for industrial and research applications. Team members collaborate closely with scientists and engineers to turn data into actionable insights that shorten development cycles. Novyte Materials offers an environment where AI and materials experts work together to push the boundaries of innovation and deliver impactful solutions.
Role Description As an AI Research Engineer at Novyte Materials, you will design, implement, and evaluate AI models to support accelerated materials discovery and optimization. Day-to-day responsibilities include developing and training machine learning and neural network architectures, building data pipelines, and performing pattern recognition on complex materials datasets. You will collaborate with materials scientists and software developers to translate research ideas into robust, production-ready tools and prototypes. The role also involves experimenting with NLP and other AI techniques, documenting research outcomes, and presenting findings to cross-functional teams. This is a full-time, on-site role based in Mumbai.
Qualifications
- Strong foundation in Machine Learning and Deep Learning.
- Demonstrated expertise in Pattern Recognition and Neural Networks, including designing, training, and optimizing models on real-world datasets.
- Proficiency in Python or similar languages, and familiarity with machine learning libraries (e.g., PyTorch, TensorFlow, scikit-learn).
- Background in or strong interest in materials science, physics, chemistry, or a related technical field is highly beneficial.
- Bachelor’s, Master’s, or PhD in Computer Science, Mathematical Optimization or Artificial Intelligence related field from a well recognised institute.
- Ability to work collaboratively in an on-site, multidisciplinary environment and communicate complex technical concepts clearly.
What you'll do:
- Read and critically analyze recent AI/ML research papers.
- Reproduce promising methods and establish strong baselines.
- Form hypotheses, design experiments, run ablations, and analyze results.
- Prototype novel architectures/algorithms and turn ideas into working implementations.
- Build reliable evaluation and benchmarking pipelines.
- Work with LLMs, multimodal models, agents, reasoning systems, retrieval/memory, and scientific AI depending on the research direction.
- Fine-tune and experiment with models using SFT/RL/post-training techniques.
- Run experiments efficiently across GPUs and distributed infrastructure.
- Maintain reproducible research code, datasets, experiment tracking, and documentation.
- Contribute toward research papers, technical reports, benchmarks and open-source releases.
A very strong fundamental in Mathematics, Probability and statistics and Deep learning is a must. I am looking for someone who enjoy understanding research papers,, questioning the existing approaches, implementing ideas from scratch.
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