Machine Learning Engineer
1 week ago
About the Role :
We're looking for a Machine Learning Engineer who doesnt just tune models for metricsbut builds systems that genuinely make people's lives easier. Youll work at the intersection of product, engineering, and research, turning ideas into intelligent systems that are production-ready, user-centric, and scalable.
This role isnt about just stacking layers in a neural netits about solving real-world problems with the right blend of models, data, and engineering Responsibilities :
- Build, train, and deploy machine learning models that solve practical, human-centered problems.- Work closely with product managers, designers, domain experts, and fellow engineers to understand requirements and design solutions.
- Own the full lifecycle of ML projects : from data gathering and preprocessing to model deployment and post-launch performance monitoring.
- Evaluate and debug models in production environmentsespecially when things go wrong unexpectedly (even at 2 AM).
- Contribute to the development of internal ML infrastructure and reusable components.
- Write clean, modular, and testable code with reproducible pipelines.
- Mentor junior engineers while remaining open to learning from more senior Qualifications :
- 24 years of hands-on experience in machine learning or data science, ideally in a production environment.- Proficiency in Python and key ML libraries such as scikit-learn, TensorFlow, PyTorch, or XGBoost.
- Experience working with cloud platforms (AWS, GCP, or Azure) and deploying models at scale.
- Strong understanding of both traditional algorithms (e.g., regression, decision trees) and modern ML techniques (e.g., transformers, CNNs, RNNs).
- Practical experience with data wrangling, feature engineering, model tuning, and performance evaluation.
- Familiarity with model versioning, monitoring, and CI/CD for ML pipelines.
(ref:hirist.tech)-
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