The role of a Machine Learning (ML) Engineer is centered around the application of machine learning algorithms and statistical models to solve real-world problems. ML engineers build and deploy models that allow systems to improve automatically through experience and data, often contributing to the development of AI (Artificial Intelligence) products.
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Design, Build, and Optimize Machine Learning Models.
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Develop predictive or classification models.
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Optimize models for scalability and performance.
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Deploy models into production.
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Collaborate with the sales team to understand client needs.
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Present technical solutions,demonstrate how they meet client objectives.
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Participate in client meetings and contribute to proposal development.
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Work with various departments, including Engineering and sales.
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Communicate complex concepts to technical stakeholders.
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Monitor and maintain live models.
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Stay current with industry trends, tools, and technologies.
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Participate in professional development opportunities.
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Bachelor’s or Master’s degree in Computer Science, Data Machine Learning, or a related field.
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3-4 years of hands-on experience in machine learning, NLP, OCR, and production environments.
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Proficiency in Python and ML frameworks like TensorFlow, PyTorch, or Keras.
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Strong experience in API development (FastAPI, Flask, or Django)
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Knowledge of queuing systems like RabbitMQ, Redis, or Celery for handling a synchronous tasks.
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Expertise in NLP techniques and OCR tools (Tesseract, OpenCV). Experience with NLP libraries (SpaCy, NLTK) and OCR frameworks.
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Familiarity with cloud platforms (AWS, Google Cloud) and MLOps practices for streamlined model deployment.
