Full-Time AI/ML Engineer

Are you passionate about designing, building, and deploying intelligent systems that deliver real value? Abstrabit is seeking a motivated and skilled AI/ML Engineer to join our growing team at our Bengaluru office.

In this role, you will be instrumental in developing and implementing sophisticated AI/ML solutions for our diverse clients. You'll work on projects involving custom chatbots, knowledge management, generative AI, and the integration of ML models into full-stack applications.

This is a fantastic opportunity for engineers with foundational experience (0-3 years) to apply their skills to challenging problems and grow within a dynamic AI consulting environment.

Responsibilities:

1. Design & Develop: Design, develop, train, and deploy machine learning models and AI solutions, including custom chatbots and knowledge-based systems.
2. Integrate Solutions: Integrate state-of-the-art AI/ML models (NLP, Computer Vision, Generative AI, etc.) into client products and internal platforms.
3. Build & Optimize: Build, manage, and continuously improve knowledge bases that power intelligent applications.
4. GenAI Implementation: Develop, fine-tune, and evaluate generative AI models and functionalities for various applications.
5. Full-Stack Contribution: Contribute to the development of full-stack applications by implementing and embedding core AI/ML features.
6. Test & Validate: Develop testing protocols, perform rigorous debugging, and ensure the performance, scalability, and reliability of AI/ML models and applications.
7. Research & Innovate: Stay current with the latest advancements in AI/ML research, tools, and techniques, evaluating their potential and applying them to solve business challenges.
8. Collaborate: Work closely with consultants, software developers, and clients to understand requirements, define solutions, and deliver impactful results.

Education: Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a closely related quantitative field.

Experience: 0-3 years of professional hands-on experience in building and deploying AI/ML models and solutions.

ML Fundamentals: Strong theoretical understanding and practical experience with core machine learning algorithms (supervised, unsupervised learning), deep learning concepts, and potentially NLP or computer vision.

Programming: Proficiency in Python is essential, along with strong experience using relevant data science and ML libraries (e.g., Pandas, NumPy, Scikit-learn).

ML Frameworks: Hands-on experience with major ML/DL frameworks such as TensorFlow, PyTorch, or Keras.

Problem Solving: Excellent analytical and problem-solving skills with meticulous attention to detail.

Communication: Strong verbal and written communication skills, with the ability to explain complex concepts clearly.

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