Research Engineer

2 weeks ago

delhi, India QpiAI Full time
Research Engineer (Scientific Deep Learning)
QpiAI is a deep tech startup pioneering next-generation computing platforms with vertical integration of AI and Quantum Computing. We are committed to accelerating 10x major advancements in drug and material design through our products and services. The ideal candidate must have deep expertise in applying deep learning techniques in Scientific Simulation Workflows.
This position is integral to supporting the Company’s growing array of products and appetite for scientific innovation. You will be a member of a multidisciplinary team working in a fast-paced startup environment. If you are motivated on building revolutionary technologies and enjoy working on ambitious projects, QpiAI is the right place for you.
Qualifications and Experience
Background in Computer science, Physics, Chemistry, Mathematics, Statistics or a related field of knowledge
Strong publication record and/or open source contributions in scientific computing
Proficiency in Software development, collaborative development in python
Experience in one or more following areas
1.Fine-tuning/Integrating Domain specific Foundation Models in scientific simulations.
2. Applying Graph Neural Networks for Molecular property Prediction, Dynamics Simulations or Generative Models
3. Integrating scientific tools with LLM Agents
4.Building AI accelerated workflows for high throughput screening for drugs/materials
In-depth understanding and hands-on experience in SOTA deep learning algorithms such as Graph Neural Networks, Transformers, Diffusion Models etc
Proficiency with deep learning frameworks (PyTorch is preferable, TensorFlow, JAX)
Desirable Skills
Can design research-grade ML experiments and ensure they can be run in a stable and repeatable manner
Broad understanding of intersection between AI and computational simulations and curiosity to build tooling around the same
Experience with MLOps best practices
Experience working with modern HPC and cloud environments
Bonus Points
PhD/Post doc experience in applying deep learning techniques in one of the areas (Computational Drug Development, Material Design , Bioinformatics )
Understanding about Quantum Computing and Quantum Algorithms
Experience with chem/material informatics and related libraries like RDKit, PyMAtgen
Exposure to data orchestration and workflow engines like Airflow, Kubeflow, Flyte, or Dagster
Experience with structured Software development, Docker, Cloud Computing
Experience managing/operating SLURM environment
Experience curating Domain Specific Datasets or Benchmarks
Experience with RAG/Agentic workflows for scientific domain.
Job Responsibilities
Co-lead the development and evaluation of the core pipelines, codebase, making advances in scientific applications. Our ideal candidate will be able to collaborate with domain scientists, and software engineers.
Develop tools and workflows that can be integrated into commercial software products
Take ownership of client facing projects, development of Proof of Concepts, and scale it to production-ready solutions for large scale deployments
Translate scientific algorithms techniques and insights into commercial applications and drive measurable business outcomes
Participate in product roadmapping to build impactful AI-for-Science products
Contribute to IP generation through Scientific publications, Patents, or software contributions
We are looking for the right teammate with a shared vision and a passion to build really impactful technology. If you feel that you fit most of our requirements but not all, please don't hesitate to apply

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