3.5–6 yrsBengaluruHybridDirect career pageEst. 10–20 LPA
Posted 15h ago
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Job description
Structured overview of role & requirements
About This Role
- Own end-to-end AI/ML model lifecycle: problem framing, data prep, model building, tuning, evaluation, and production deployment.
- Collaborate with business and product teams to define ML tasks with clear success metrics, and communicate results to non-technical stakeholders.
- Mentor junior members and contribute to code reviews and best practices while maintaining scalable training and data pipelines.
Minimum Requirements
- 4 years of hands-on experience building and training ML/AI models; at least 2 models deployed to production.
- Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Mathematics, or related field.
- Proficient in Python with pandas, NumPy, scikit-learn; deep learning experience with PyTorch or TensorFlow/Keras, including custom training loops and architectures.
- Experience with NLP or computer vision, transformer models (e.g., Hugging Face), fine-tuning LLMs, SQL, large data sets, experiment tracking (MLflow, Weights & Biases), Git, and cloud GPU training (AWS SageMaker, Azure ML, or GCP Vertex AI).
Ideal Candidate Profile
- Experienced in full ML lifecycle including experiment design, model optimization (speed, cost, memory) and production deployment in cloud environments.
- Able to translate business problems into ML tasks and communicate results effectively to non-technical teams.
- Has mentored junior team members and driven best practices in code quality and reproducible model workflows.