Machine Learning Engineer

Machine Learning Engineer (Entry-Level)

About the Role

We are seeking highly motivated and technically skilled Machine Learning Engineers to join our growing team in the USA. This opportunity is ideal for candidates passionate about Artificial Intelligence, Deep Learning, Generative AI, Predictive Analytics, and building scalable intelligent systems.

The selected candidate will collaborate closely with data scientists, software engineers, AI researchers, and business stakeholders to develop, deploy, and optimize machine learning models that solve complex business challenges.

Key Responsibilities

• Design, develop, and deploy cutting-edge machine learning and AI solutions.
• Build predictive models, recommendation systems, and intelligent automation tools.
• Analyze and process large structured and unstructured datasets to derive insights.
• Develop robust feature engineering and data preprocessing pipelines.
• Train, evaluate, tune, and optimize deep learning algorithms for production environments.
• Collaborate with engineering teams to integrate ML models seamlessly into existing software stacks.
• Monitor model performance, ensuring scalability, reliability, and fairness in real-world applications.
• Support cloud deployment strategies (AWS/Azure/GCP) and implement MLOps best practices.
• Research and implement emerging technologies including LLMs, NLP, Computer Vision, and Generative AI.

Required Qualifications

• Education: Master's Degree in Machine Learning, Artificial Intelligence, Computer Science, Data Science, Statistics, Mathematics, or a related quantitative field (Mandatory).
• Experience: 0–3 years of hands-on experience with ML/AI projects.
• Core Skills: Strong foundation in machine learning algorithms, statistical probability, linear algebra, and data structures.
• Soft Skills: Excellent analytical problem-solving abilities and clear technical communication skills.

Preferred Technical Stack

We highly value proficiency in the following technologies:

• Languages: Python (Primary), SQL
• Framworks & Libraries: TensorFlow, PyTorch, Scikit-learn
• Cloud Platforms: AWS, Azure, Google Cloud Platform
• Concepts: MLOps Fundamentals, Data Engineering Principles, Containerization (Docker/Kubernetes)