Machine Learning Intern

Full Description

Job Overview:

As a Machine Learning Engineering Intern, you will work closely with our experienced team of machine learning engineers and data scientists to design, implement, and optimize machine learning models. You’ll gain hands-on experience in deploying real-world ML systems and contribute to projects that impact both internal stakeholders and end-users.

Key Responsibilities:

• Assist in thedesign, development, and deployment of machine learning models and algorithms.

• Work with large datasets to clean, process, and analyze data.

• Collaborate with cross-functional teams (data scientists, software engineers, product managers) to integrate machine learning models into production systems.

• Evaluate model performance using appropriate metrics and make improvements where necessary.

• Conduct exploratory data analysis (EDA) to identify trends, patterns, and outliers.

• Assist with optimizing ML pipelines for scalability and performance.

• Stay up-to-date with the latest research and developments in machine learning.

Requirements:

• Currently pursuing a degree in Computer Science, Engineering, Mathematics, Statistics, or a related field.

• Strong understanding of machine learning algorithms (e.g., supervised, unsupervised learning, deep learning).

• Proficiency in programming languages such as Python, R, or Java.

• Familiarity with machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn).

• Knowledge of data manipulation and analysis using libraries like Pandas, NumPy, and SQL.

• Understanding of model evaluation techniques (e.g., cross-validation, ROC curves, etc.).

• Familiarity with cloud platforms (AWS, Google Cloud, or Azure) is a plus.

• Strong problem-solving skills and a passion for learning new technologies.

• Excellent communication and collaboration skills.

Preferred Qualifications:

• Experience with deploying machine learning models in a production environment.

• Exposure to tools for version control, such as Git.

• Understanding of distributed computing frameworks (e.g., Apache Spark, Hadoop) is a bonus.

• Interest in specific application areas like Natural Language Processing, Computer Vision, or Reinforcement Learning is a plus.

What We Offer:

• Mentorship from experienced engineers and researchers.

• Hands-on experience working on real-world ML projects.

• Exposure to the latest ML techniques and tools.

• A collaborative and dynamic work environment.

• Potential for full-time offers based on performance.

Created at 2025-04-03 11:21:44

Updated at 2025-04-04 07:30:23

Location: In-office (Hyderabad, Pakistan);

About Deccan AI:

About Deccan AI

Deccan AI is at the forefront of building superior Large Language Models (LLMs) and Foundational Models, driven by high-quality human data. We believe that a model is only as good as its data, and the data is only as good as the humans behind it.

Why Join Us?

• Be part of a pioneering team in the AI Data Building.

• Work with cutting-edge technology and contribute to the development of superior LLMs.

• Join a close-knit team of 50 dedicated professionals.

• Make a significant impact in a company that values high-quality human data.

Our Culture

At Deccan AI, we foster a culture of innovation, collaboration, and excellence. Our team is passionate about pushing the boundaries of technology and creating models that make a difference. We value diversity, creativity, and the unique contributions of each team member.

Current Opportunities

Explore our current job openings and find your next career opportunity with Deccan AI. We are always looking for talented individuals who are eager to make an impact in the world of AI and software development.

Contact Us

Interested in joining our team? Reach out to us at hr@deccan.ai for more information about our current openings and the application process.

companyDescription: We're a young and lightning-fast team based out of SF and Hyderabad. We're on a mission to build AI for Good. We are building next generation of company that will enable deployments of LLMs with confidence.

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