Artificial Intelligence Engineer
2 days ago
Company Description
SkureLabs is a cybersecurity company dedicated to making advanced protection accessible to everyone. By combining traditional security practices with cutting-edge AI technology, SkureLabs aims to provide comprehensive protection against sophisticated cyber threats. At SkureLabs, we believe that cybersecurity is a fundamental right, not a privilege. We are a deep-tech product company committed to making advanced, AI-powered security accessible to all—from individuals and startups to large enterprises and public institutions. Our mission is to protect digital communication and infrastructure through intelligent, scalable, and locally supported cybersecurity solutions.
Role Description
This is a full-time, hybrid/remote role located in Pune for an Artificial Intelligence Engineer. The AI Engineer will be responsible for designing, developing, and implementing AI-based solutions to address complex cybersecurity challenges. Daily tasks will include working on pattern recognition algorithms, neural network development, natural language processing (NLP), and software development. The role requires collaboration with other team members to enhance the functionality and security of SkureLabs' products.
Qualifications
- 3+ years of experience in AI/ML engineering, with a minimum of 2 years focused on NLP or generative AI.
- Strong knowledge of Computer Science
- Experience in Software Development
- Proficiency in
Natural Language Processing (NLP) - Excellent problem-solving and analytical skills
- Bachelor's or Master's degree in Computer Science, Engineering, or related field
- Pattern Recognition
and
Neural Networks skills. - Knowledge of
Python
is mandatory. - Strong programming skills with expertise in libraries like
PyTorch
/
TensorFlow
,
Hugging Face Transformers, scikit-learn, and imbalanced-learn. - Hands-on experience with foundation models (e.g.,
BERT, Llama
) and agentic frameworks (e.g., LangChain). Understanding of
prompt engineering, fine-tuning
, and
RAG
(Retrieval-Augmented Generation). - Proven ability to handle imbalanced datasets, evaluate model performance (e.g., precision, recall, F1-score), and apply advanced techniques like weighted loss functions or ensemble methods.
- Experience with production deployment using tools like Docker, FastAPI/
Flask.
Familiarity with MLOps practices. - Strong problem-solving abilities to diagnose and resolve performance issues, with a focus on delivering high-quality, production-ready solutions.
Good to have
- Experience in the cybersecurity domain, including familiarity with threat intelligence, malware analysis, or security tools (SIEM, EDR).
- Knowledge of adversarial machine learning or experience with reverse engineering tools (e.g., Ghidra).
- Knowledge of other programming language like Go and No-SQL databases.
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