Ai Ml Engineer

Job Description

LeadSquared is looking for a passionate and driven Machine Learning Engineer with 1–2 years of experience to join our innovative engineering team in Bengaluru.

This role primarily focuses on developing, deploying, and maintaining machine learning models. The ideal candidate will also have a basic understanding of data engineering concepts and be comfortable working with data pipelines.

You will collaborate closely with data scientists, engineers, and product teams to convert business problems into scalable, production-ready ML solutions.

🛠️ Key Responsibilities

• Participate in the end-to-end ML lifecycle: problem definition, modeling, deployment, and monitoring
• Develop and implement machine learning models using appropriate algorithms and techniques
• Experiment with multiple modeling approaches and evaluate model performance
• Collaborate with data scientists on feature engineering and data preparation
• Assist in data cleaning, preprocessing, and validation for training and evaluation
• Deploy and maintain ML models in production environments
• Monitor model performance and retrain models when required
• Contribute to MLOps pipelines and ML best practices
• Work with cloud platforms such as AWS, Azure, or GCP and their ML services
• Document ML experiments, models, and deployment workflows
• Stay updated with the latest ML tools, techniques, and research
• Work with cross-functional teams to integrate ML solutions into products
• Troubleshoot and resolve issues related to deployed ML systems

🎯 Required Qualifications & Skills

Must-Have

• Bachelor’s degree in Engineering
• 1–2 years of hands-on experience in Machine Learning
• Strong understanding of ML concepts, algorithms, and evaluation metrics
• Proficiency in Python
• Hands-on experience with:
  • Scikit-learn
  • TensorFlow
  • PyTorch
• Experience with Pandas, NumPy, and data processing libraries
• Strong analytical and problem-solving skills
• Good communication and collaboration abilities

Good-to-Have

• Basic understanding of data engineering principles
• Exposure to data pipelines
• Familiarity with relational databases or data lakes
• Experience with cloud ML services:
  • AWS SageMaker
  • Azure ML
  • Google Vertex AI
• Awareness of MLOps concepts

🔑 Key Skills

Machine Learning | Python | TensorFlow | PyTorch | Scikit-learn | Pandas | NumPy | MLOps | Cloud ML | Data Pipelines