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KeyValue Software Systems - AI Engineer - NLP/Python

Posted on: 30/10/2025

Job Description

Description :

- We are looking for a talented and motivated Machine Learning Engineer to join our growing team.

- In this role, you will play a key part in designing, developing, and deploying machine learning models to solve complex business problems.

- You will work closely with data scientists, software engineers, and product managers to bring innovative solutions to life.

What You Will Do :

- Design, develop, and deploy machine learning models for various applications (e.g., recommendation systems, fraud detection, natural language processing).

- Collaborate with data scientists to understand business requirements, translate them into technical specifications, and select appropriate algorithms.

- Prepare and clean data for training and evaluation of machine learning models.

- Train, test, and evaluate machine learning models to ensure accuracy, efficiency, and scalability.

- Monitor and maintain deployed models in production, and identify opportunities for improvement.

- Stay up-to-date on the latest advancements in machine learning research and best practices.

- Communicate effectively with technical and non-technical audiences to explain complex concepts.

What makes you a great fit ? :

- 3-7 years of experience in machine learning engineering.

- Proven experience in building and deploying machine learning models.

- Strong understanding of machine learning algorithms and techniques (e.g., supervised learning, unsupervised learning, deep learning).

- Proficiency in Python.

- Experience with machine learning libraries and frameworks (e.g., TensorFlow, PyTorch, scikit-learn).

- Strong understanding of machine learning algorithms and techniques, as well as LLM architecture and functionalities.

- Excellent problem-solving and analytical skills.

- Strong communication and collaboration skills.

Bonus Points :

- Experience with cloud platforms (e.g., AWS, GCP, Azure).

- Experience with MLOps tools and methodologies.

- Open-source contributions.


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