Truecaller - Machine Learning Engineer - LLM Models
2 weeks ago
Note : If shortlisted, you will be invited for initial rounds on 13th September'25 (Saturday) in Bengaluru
As an ML Engineer, you will be responsible for collecting, organizing, analyzing, and interpreting Truecaller data with a focus on NLP. In this role, you will be working hands-on to optimize the training and deployment of ML models to be quick and cost-efficient.
Also, you will be pivotal in advancing our work with large language models and in-device models across diverse regions. Your expertise will enhance our natural language processing, machine learning, and predictive analytics capabilities.
What you bring in :
- 3+ years in machine learning engineering, with hands-on involvement in feature engineering, model development, and deployment.
- Experience in Natural Language Processing (NLP), with a deep understanding of text processing, model development, and deployment challenges in the domain.
- Proven ability to develop, deploy, and maintain machine learning models in production environments, ensuring scalability, reliability, and performance.
- Strong familiarity with ML frameworks like TensorFlow, PyTorch, and ONNX, and experience in tech stack such as Kubernetes, Docker, APIs, Vertex AI, GCP.
- Experience deploying models across backend and mobile platforms.
- Fine-tune and optimize LLMs prompts for domain-specific applications
- Ability to optimize feature engineering, model training, and deployment strategies for performance and efficiency.
- Strong SQL and statistical skills.
- Programming knowledge in at least one language, such as Python or R. Preferably python.
- Knowledge of machine learning algorithms.
- Excellent teamwork and communication skills, with the ability to work cross-functionally with product, engineering, and data science teams.
- Good to have the knowledge in retrieval-based pipelines to enhance LLM performance
The impact you will create :
- Collaborate with Product and Engineering to scope, design, and implement systems that solve complex business problems ensuring they are delivered on time and within scope.
- Design, develop, and deploy state-of-the-art NLP models, contributing directly to message classification and fraud detection at scale for millions of users.
- Leverage cutting-edge NLP techniques to enhance message understanding, spam filtering, and fraud detection, ensuring a safer and more efficient messaging experience.
- Build and optimize ML models that can efficiently handle large-scale data processing while maintaining accuracy and performance.
- Work closely with data scientists and data engineers to enable rapid experimentation, development, and productionization of models in a cost-effective manner.
- Streamline the ML lifecycle, from training to deployment, by implementing automated workflows, CI/CD pipelines, and monitoring tools for model health and performance.
- Stay ahead of advancements in ML and NLP, proactively identifying opportunities to enhance model performance, reduce latency, and improve user experience.
- Your work will directly impact millions of users, improving message classification, fraud detection, and the overall security of messaging platforms.
It would be great if you also have:
- Understanding of Conversational AI
- Deploying NLP models in production
- Working knowledge of GCP components
- Cloud-based LLM inference with Ray, Kubernetes, and serverless architectures
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