Senior machine learning researcher
2 weeks ago
Job Title - Senior Machine Learning Researcher Job Location - Pune, Maharashtra (offers Remote friendly work option) Company Description Our client is a product engineering company working with innovative startups and enterprises.
They have provided core product development for 110+ startups across the globe building products in the cloud-native, data engineering, B2 B Saa S & Machine Learning space.
Their team of 400+ elite software & Dev Ops engineers solve hard technical problems while transforming customer ideas into successful products.
Role Overview As a Sr.
Machine Learning Researcher specializing in security, you will apply your expertise in machine learning and cybersecurity to develop innovative solutions to detect, prevent, and respond to security threats and fraud.
You will conduct independent research, collaborate with cross-functional teams, and stay abreast of the latest advancements in the field.
Key Responsibilities: Develop and implement ML and deep learning models to detect and mitigate security threats.
Developing 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.
Technical Skills: Bachelors, Masters or Ph D 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., Tensor Flow, Py Torch, 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.
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