Arbetsbeskrivning

We are looking for a passionate and curious Entry-Level Machine Learning Engineer & Developer to join our AI and Data team. In this role, you’ll contribute to building intelligent systems and data-driven applications by assisting in the development, training, deployment, and monitoring of machine learning models. This is a hands-on learning opportunity for someone eager to grow into a full-stack ML engineering role.

Key Responsibilities

Model Development & Research

• Assist in developing and training ML models for tasks like prediction, classification, recommendation, or NLP.
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• Experiment with different algorithms using real-world datasets under the guidance of senior team members.
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• Perform data exploration, preprocessing, feature engineering, and visualization.

Engineering & Automation

• Support the creation of end-to-end ML workflows and basic data pipelines.
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• Contribute to deploying ML models into production environments using APIs or automation scripts.
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• Work with containerized environments (e.g., Docker) and version control systems (e.g., Git).

Learning & Collaboration

• Participate in code reviews, brainstorming sessions, and research discussions.
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• Document your experiments, learnings, and processes clearly for reproducibility and team sharing.
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• Learn best practices in software development, ML experimentation, and model evaluation.

Monitoring & Maintenance

• Help in testing, validating, and monitoring deployed models and data pipelines.
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• Identify potential issues like data drift or performance degradation.

Required Qualifications

• Bachelor's degree in Computer Science, Data Science, Engineering, Statistics, or a related field.
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• Strong programming skills in Python.
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• Basic understanding of machine learning concepts and algorithms (e.g., linear regression, decision trees, clustering, etc.).
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• Exposure to libraries like scikit-learn, pandas, NumPy, or TensorFlow/PyTorch (via academic projects, internships, or personal work).
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• Familiarity with basic software engineering tools: Git, Jupyter Notebooks, or simple APIs.

Preferred Qualifications

• Internship or academic project experience involving machine learning or data science.

• Knowledge of SQL and cloud environments (AWS, Azure, or GCP) is a plus.

• Understanding of REST APIs or experience in integrating models into applications.
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• Interest in MLOps concepts like model versioning, CI/CD for ML, and model monitoring.

What You’ll Gain

• Mentorship from experienced engineers and data scientists.

• Practical experience working on real-world ML problems.

• Access to state-of-the-art tools, cloud resources, and continuous learning opportunities.

• A collaborative, inclusive team environment with room for career growth.