We are looking for an exceptional technical leader to join our growing team at Nightfall.

As a Lead Applied Scientist joining the AI Engineering organisation, you will create ML/NLP models and Gen AI solutions that power our Data Leak Protection (DLP) and other Security products.

You will provide technical guidance to ML engineers build the production systems, and help shape the long-term architecture of the AI Platform.

This is a hybrid role (2-day office) based out of our Bangalore office, and a perfect opportunity to pursue your passion for Data Science and ML engineering.

Responsibilities :

- Fast-paced, hands-on execution, work with the team to set clear goals, and deliver against them.

- Apply statistical and machine learning techniques to come up with creative solutions for detecting and solving problems in the enterprise security space.

- Create, train and fine-tune NLP, large language and other models for use in large-scale, real-time environments.

- Work with the team to take model prototypes to production through the entire ML lifecycle phases: system architecture, data creation, training, inferencing and evaluation.

- Help shape the architecture of the AI Models and Platform to support machine learning at scale and with optimal operational cost.

- Champion a culture of data and impact-driven engineering.

Requirements :

- Minimum 5+ years of hands-on, technical development experience

- 5-10 years of experience mentoring and technically leading Data Science or ML Engineering teams.

- Strong expertise in Python with an additional language such as Go, C++, Java or Rust.

- Knowledge of data structures and algorithms is a must.

- Grounded in Data Science and Machine Learning algorithms with demonstrated business impact (preferably in security or related domain) through application of statistical and machine learning techniques.

- Proficient in training custom transformers, large language models or other deep learning models to solve complex NLP problems, and designing the ML systems to host models in production.

- BS/MS/Ph.D. in Computer Science, Applied Math, or a related technical field.

Bonus Points :

- Experience working in high-growth venture-backed startups.

- Prior experience using AI in Security : Detection of Health, Named Entity, PII data, modelling security risk, etc.

- ML training and inferencing at scale with hands-on experience with horizontal and vertical scaling, including the use of GPUs.

- Experience with prompt and context engineering for LLMs, RAG/vector databases, and conversational/agentic frameworks is a plus.

- Experience with ML frameworks such as Sagemaker, MLflow, Vertex AI, etc.

- Blog, teach, mentor, or help others learn outside of your day-to-day responsibilities.

- Familiarity with AWS and managed infrastructure