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Company Description
EveningsideLabs is an emerging technology company focused on building practical, high-impact AI solutions for real-world problems. The team combines strong engineering practices with cutting-edge research to deliver products that are reliable, scalable, and easy to use. Collaboration, experimentation, and continuous learning are central to how the company operates. EveningsideLabs offers opportunities to work on innovative projects, contribute to core product decisions, and grow alongside a fast-evolving AI ecosystem.
Role Description
The AI Engineer will design, develop, and deploy machine learning and AI models that power core products and internal tools. Day-to-day responsibilities include:
- Researching and experimenting with new algorithms
- Building and training models
- Evaluating performance
- Iteratively improving solutions based on data and user feedback
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The role involves close collaboration with software engineers and product teams to integrate AI components into production systems, maintain model pipelines, and ensure robust monitoring and scalability. This is a full-time, hybrid role based in Ahmedabad, with a mix of on-site collaboration and some work-from-home flexibility.
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Qualifications
- Strong foundation in Computer Science and Software Development, including data structures, algorithms, and version control.
- Experience with Pattern Recognition and Neural Networks for building and optimizing machine learning models.
- Hands-on expertise with Natural Language Processing (NLP), including model training, evaluation, and deployment for text-related tasks.
- Proficiency in programming languages commonly used in AI (such as Python), and frameworks like TensorFlow, PyTorch, or similar.
- Familiarity with data processing, model evaluation metrics, and experimentation workflows.
- Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, or a related field, or equivalent practical experience.
- Ability to work in a hybrid setup in Ahmedabad, communicate clearly with cross-functional teams, and manage time across research and implementation tasks.
- Experience with cloud platforms, MLOps practices, or deploying models to production environments is a plus.
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