Machine 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 highly motivated Machine Learning Scientist to lead cutting-edge computational projects at the intersection of biology, chemistry, and data science. In this role, you will develop, implement, and optimize machine learning models—including neural networks—to analyze complex data sets such as GC-MS outputs, genomic data, and other biological/chemical datasets. Your work will directly contribute to groundbreaking innovations in cancer and human longevity.

**Responsibilities**:

- **Data Acquisition & Management**:

- Collect, organize, and preprocess large-scale biological datasets.
- Implement workflows for data cleaning, quality control, and normalization.
- **Algorithm & Model Development**:

- Design and train machine learning/deep learning models (e.g., neural networks, convolutional networks, transformer-based architectures) to interpret complex chemical and biological data.
- Continuously iterate and improve algorithms for higher accuracy and performance.
- **Computational & Bioinformatics Analysis**:

- Develop and maintain pipelines for data processing, integration, and annotation.
- Conduct bioinformatics analyses (e.g., metabolomics, proteomics, structural predictions) to derive meaningful biological and/or chemical insights.
- Work closely with cross-functional teams (e.g., wet-lab scientists, chemists, R&D engineers) to interpret and validate computational predictions.
- **Infrastructure & Deployment**:

- Collaborate with IT/Engineering teams to ensure models can be efficiently trained and deployed on scalable computing resources (on-premises or cloud-based).
- Implement best practices for reproducibility, version control, and containerization to streamline deployment of solutions.
- **Research & Innovation**:

- Stay current on latest machine learning and bioinformatics research, integrating relevant breakthroughs into ongoing projects.
- Propose and pilot new analytical methods, tools, and models that push the boundaries of what’s possible in computational biology and chemistry.
- Author technical reports, white papers, and/or peer-reviewed publications, as appropriate.
- **Collaboration & Communication**:

- Provide clear updates on progress, challenges, and milestones to stakeholders across the organization.
- Contribute to strategic planning, aligning projects with broader company goals.

**Qualifications**:

- **Education**:

- Ph.D. or Master’s in Bioinformatics, Computational Biology, Computer Science, Data Science, or a related discipline. Equivalent experience will be considered.
- **Technical Skills**:

- Proficiency in Python, R, or similar high-level programming languages.
- Experience with machine learning/deep learning frameworks (e.g., TensorFlow, PyTorch, scikit-learn).
- Solid understanding of bioinformatics workflows, databases, and analysis tools.
- Familiarity with GC-MS, LC-MS, or other mass spec data analysis is strongly preferred.
- Experience with version control (Git) and containerization (Docker) is a plus.
- **Analytical & Domain Knowledge**:

- Strong background in statistics, data modeling, and algorithmic thinking.
- Understanding of omics data (genomics, proteomics, metabolomics) and structural biology concepts.
- Demonstrated ability to interpret and visualize complex datasets, drawing actionable insights.
- **Soft Skills**:

- Excellent communication skills, with the ability to distill complex analyses into clear, actionable information.
- Proven track record of collaboration in cross-functional teams.
- Self-motivated, detail-oriented, and capable of managing multiple projects simultaneously.

**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 - ₹7,835,665.00 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