ML Engineer - II
Bengaluru-VTP, India
Groww
Start Online Investing in Stocks & Direct Mutual Funds with India's No. 1 Stock Broker - Groww. Equity Trading, F&O, Direct Mutual Funds with Zero-commission & 24x7 support.- Radical customer centricity
- Ownership-driven culture
- Keeping everything simple
- Long-term thinking
- Complete transparency
Key Responsibilities:
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Design and implement scalable machine learning solutions aligned with product and business objectives
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Develop, test, and optimize ML models for deployment in production environments
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Contribute to the development of Generative AI features such as conversational interfaces and personalization modules
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Collaborate with product managers, data scientists, and engineers to integrate ML solutions into customer-facing products
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Monitor performance of deployed models and iterate to improve accuracy, latency, and user experience
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Follow best practices in model development, experimentation, and deployment
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Participate in code reviews, technical discussions, and architectural design sessions
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Translate business requirements into technical specifications in partnership with stakeholders
Required Skills and Experience:
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4–5 years of experience in applied machine learning and model deployment
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Hands-on experience with Generative AI, NLP, or conversational AI technologies
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Proficiency in Python and commonly used ML frameworks (e.g., PyTorch, TensorFlow, Hugging Face)
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Experience building and deploying models using cloud services (AWS, GCP, or Azure)
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Strong grasp of ML pipelines, feature engineering, and basic MLOps practices
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Ability to work collaboratively and communicate technical concepts clearly
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Experience contributing to production-level ML solutions that deliver measurable value
Preferred Qualifications:
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Master’s degree in Computer Science, Machine Learning, or related discipline
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Exposure to fintech or financial services domain is a plus
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Familiarity with recommendation engines or personalization techniques
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Contributions to open-source ML projects or community
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Experience with model monitoring, CI/CD for ML, and versioning tools like MLflow or Kubeflow
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: AWS Azure CI/CD Computer Science Conversational AI Engineering Feature engineering FinTech GCP Generative AI Kubeflow Machine Learning MLFlow ML models MLOps Model deployment NLP Open Source Pipelines Python PyTorch TensorFlow
Perks/benefits: Career development Transparency
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