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Lead Mobile Developer, Android

Lead Mobile Developer, Android

F-secure

3 - 6 years

5 - 8 Lacs

bengaluru

Posted:1 week ago| Platform:

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Skills Required

usage cyber security gcp neural networks machine learning debugging agile monitoring python android

Work Mode

Work from Office

Job Type

Full Time

Job Description

About the role

We are looking for skilled

Machine Learning Engineers

to join our Technology team in Bengaluru! At F-Secure, were developing cutting-edge AI-powered cybersecurity defenses that protect millions of users globally. Our ML models operate in dynamic environments where threat actors continuously evolve their techniques.

Were seeking a motivated individual to perform in-depth analysis of data and machine learning models, develop and implement models using both classical and modern approaches, and optimize models for performance and latency. This is a fantastic opportunity to enhance your skills in a real-world cybersecurity context with significant impact.

This role will be located in Bengaluru, India. You can choose whether you work at our Bengaluru office, or in a hybrid mode from your home office. We hope you are able to join us for common gatherings at the Bengaluru office when needed.

Key responsibilities:

To perform in-depth analysis of data and machine learning models to identify insights and areas of improvement.
Develop and implement models using both classical machine learning techniques and modern deep learning approaches.
Deploy machine learning models into production, ensuring robust MLOps practices including CI/CD pipelines, model monitoring, and drift detection.
Conduct fine-tuning and integrate Large Language Models (LLMs) to meet specific business or product requirements.
Optimize models for performance and latency, including the implementation of caching strategies where appropriate.
Collaborate cross-functionally with data scientists, engineers, and product teams to deliver end-to-end ML solutions.

What are we looking for

Prior experience from utilizing various statistical techniques to derive important insights and trends.
Proven experience in machine learning model development and analysis using classical and neural networks based approaches.
Strong understanding of LLM architecture, usage, and fine-tuning techniques.
Solid understanding of statistics, data preprocessing, and feature engineering.
Proficient in Python and popular ML libraries (scikit-learn, PyTorch, TensorFlow, etc.).
Strong debugging and optimization skills for both training and inference pipelines.
Familiarity with data formats and processing tools (Pandas, Spark, Dask).
Experience working with transformer-based models (e g, BERT, GPT ) and Hugging Face ecosystem.

Additional nice-to-haves:

Experience with MLOps tools (e g, MLflow, Kubeflow, SageMaker, or similar).
Experience with monitoring tools (Prometheus, Grafana, or custom solutions for ML metrics).
Familiarity with cloud platforms (Sagemaker, AWS, GCP, Azure) and containerization (Docker, Kubernetes).
Hands-on experience with MLOps practices and tools for deployment, monitoring, and drift detection.
Exposure to distributed training and model parallelism techniques.
Prior experience in AB testing ML models in production.

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Lead Mobile Developer, Android