At a glance
- Workplace
- Hybrid
- Location
- Pune · India
About the role
- The Senior Machine Learning Researcher will apply expertise in machine learning and cybersecurity to develop innovative solutions for detecting, preventing, and responding to security threats and fraud.
- The role involves conducting independent research, collaborating with cross-functional teams, and integrating ML solutions into security products to protect global enterprise clients.
Responsibilities
- Develop and implement ML and deep learning models to detect and mitigate security threats.
- Develop new product features using statistical/machine learning-based algorithms to identify bot and fraud traffic.
- Conduct data cleaning, preprocessing, and exploratory data analysis.
- Apply statistical methods to analyze security-related data.
- Stay updated with the latest research and advancements in ML and cybersecurity.
- Publish research findings in reputable journals and conferences.
- Collaborate with cross-functional teams to understand project requirements and contribute to the development of solutions.
- Collaborate with security analysts, software engineers, and other stakeholders to integrate ML solutions into security products.
- Communicate complex technical concepts to both technical and non-technical stakeholders effectively.
Requirements
- Bachelor's, Master's, or PhD in Computer Science, Machine Learning, Artificial Intelligence, or a related field.
- Proficiency in ML algorithms, neural networks, and model development.
- Experience with ML frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn).
- Strong coding skills in Python, R, and familiarity with languages such as C++, Java, or Scala.
- Ability to perform data cleaning, preprocessing, and exploratory data analysis.
- Strong understanding of statistical methods and their applications.
- Familiarity with cybersecurity concepts, threat models, and common attack vectors.
- Experience with security tools and technologies (e.g., intrusion detection systems, firewalls, malware analysis tools).
- Strong analytical and problem-solving skills to identify and mitigate security threats using ML techniques.
- Understanding of network security, bot security, application security, and incident response.
Preferred qualifications
- Experience with bot detection, device fingerprinting, behavioral biometrics, or real-time risk scoring.
- Experience with low-latency, high-throughput ML serving infrastructure.
- Familiarity with current ML research relevant to fraud/security (e.g., following or contributing to arXiv publications in adversarial ML, anomaly detection, or graph learning).
- Experience scaling researcher productivity using Agentic AI.
Benefits
- Competitive salary
- Equity
- Beautiful office space with perks
- Robust benefits package
- Provident Fund
- Accident Insurance
- Support for continuing education
Workplace
- Hybrid office model
- Flexible working hours
- Work from home days
Skills
- Python
- R
- C++
- Java
- Scala
- TensorFlow
- PyTorch
- Scikit-learn
- Deep Learning
- Statistical Methods
- Cybersecurity
- Bot Detection
Show all 15 skills
- Anomaly Detection
- Graph Learning
- Agentic AI
