Deep Learning Scientist

**Company Overview**

Grafton Biosciences is a US-based biotech startup (with offices in Bengaluru) focused on solving cancer and cardiovascular disease through groundbreaking innovations in early detection, diagnostics, and therapeutics. We combine cutting-edge molecular and synthetic biology, machine learning, device engineering, and manufacturing to deliver transformative solutions. Many previous attempts to solve cancer have come up short - we intend to be the first to _actually _solve it. We’re looking for passionate team members who want to shape the future of medicine.

**Role Overview**

We are seeking a Senior Deep Learning Scientist to spearhead the design, development, and implementation of advanced neural network architectures for next-generation cancer detection solutions. In this role, you will work with a variety of large-scale data sources and leverage cutting-edge deep learning techniques to drive breakthrough innovations.

**Responsibilities**:
1. **Neural Network Architecture & Model Development**
- Design and optimize state-of-the-art neural network models (e.g., CNNs, RNNs, transformers, or custom architectures) tailored to complex data and challenging predictive tasks.
- Implement best practices in model training, validation, and deployment, ensuring performance, scalability, and reliability.

2. **Research & Innovation**
- Stay abreast of the latest research in deep learning, contributing new ideas and methods to enhance model accuracy, generalizability, and interpretability.
- Rapidly prototype new approaches, evaluate their effectiveness, and iterate for continuous improvement.

3. **Data Management & Processing**
- Collaborate with data engineering teams to establish data pipelines for large, heterogeneous datasets.
- Develop efficient data preprocessing, augmentation, and feature engineering techniques for high-quality model inputs.

4. **Infrastructure & Scalability**
- Work with DevOps or IT to utilize cloud-based or on-premise GPU/TPU environments for distributed training and large-scale inference.
- Optimize code and workflows to fully leverage hardware accelerators, ensuring mínimal training/inference times.

5. **Cross-Functional Collaboration**
- Partner with domain experts (e.g., clinicians, biologists, product managers) to understand problem requirements and translate them into technical roadmaps.
- Provide guidance and mentorship to junior team members and interns on deep learning methodologies and best practices.

6. **Results Communication**
- Present project updates and breakthroughs to both technical and non-technical audiences.
- Document research findings, methodologies, and outcomes in technical reports or publications, as appropriate.

**Qualifications**:

- **Education & Experience**
- Ph.D. or Master’s degree in Computer Science, Data Science, Applied Mathematics, or related field (or equivalent industry experience).
- **Technical Expertise**
- Proficiency with leading deep learning frameworks (e.g., PyTorch, TensorFlow, JAX).
- Extensive hands-on experience designing, training, and deploying advanced neural network architectures.
- Strong background in Python (preferred) or other relevant programming languages (e.g., C++).
- Familiarity with distributed training, mixed-precision, and HPC/cloud-based computing environments.
- **Analytical & Mathematical Skills**
- Solid understanding of linear algebra, probability/statistics, and optimization.
- Ability to evaluate the trade-offs of various model architectures and hyperparameter tuning approaches.
- **Soft Skills**
- Excellent communication and interpersonal skills; ability to simplify complex technical concepts for broader audiences.
- Self-motivated problem solver who thrives in a collaborative, fast-paced, and innovative environment.

**Why Join Us**
- Opportunity to lead high-impact, well-funded biotech projects with the potential to transform patient care.
- Collaborative environment that values innovation, scientific rigor, and professional growth.
- Competitive compensation package, including benefits and ample opportunities for career advancement.

Pay: ₹2,611,977.00 - ₹9,535,665.00 per year

Supplemental Pay:

- Performance bonus

Application Question(s):

- In 4 sentences or less, tell us why we should hire you?
- In 4 sentences or less, feel free to tell us anything. Maybe something you'd like to highlight. Or something that your resume may not capture. If nothing, write N/A.

Work Location: In person