Job Description

This role is for one of Weekday's clients
Min Experience: 3 years
Location: Karnataka
JobType: full-time
Requirements
We are seeking a skilled and innovative Machine Learning (ML) Engineer with a minimum of 3 years of experience in designing, building, and deploying ML models and solutions. The ideal candidate will have strong expertise in machine learning algorithms, data preprocessing, model training, and production deployment. You will collaborate closely with data scientists, data engineers, and software developers to deliver high-performing, scalable ML solutions that drive business impact.
Key Responsibilities

• Model Development & Deployment

• Design, develop, and implement machine learning models tailored to business requirements.
• Work on end-to-end ML lifecycle including data preprocessing, feature engineering, model selection, training, validation, and deployment.
• Optimize models for performance, accuracy, and scalability in production environments.
• Data Engineering & Processing

• Collaborate with data engineers to ensure robust data pipelines for structured and unstructured data.
• Perform data wrangling, cleaning, and feature extraction to prepare high-quality datasets.
• Implement ETL workflows to ensure data is readily available for ML tasks.
• Collaboration & Stakeholder Management

• Partner with product managers, business analysts, and domain experts to translate business problems into ML solutions.
• Collaborate with cross-functional teams to integrate ML models into existing applications, platforms, or workflows.
• Provide technical guidance to junior engineers and contribute to knowledge-sharing within the team.
• Research & Innovation

• Stay updated on the latest research, tools, and frameworks in machine learning, deep learning, and AI.
• Experiment with cutting-edge techniques such as NLP, computer vision, or reinforcement learning when relevant to business needs.
• Continuously improve ML infrastructure, monitoring, and automation to increase efficiency.
• Testing, Monitoring & Maintenance

• Implement rigorous testing methodologies including A/B testing, model validation, and bias detection.
• Monitor model performance post-deployment to ensure stability and reliability over time.
• Troubleshoot and retrain models as required to maintain accuracy in dynamic environments.

Required Skills & Qualifications

• Bachelor's or Master's degree in Computer Science, Data Science, AI, or a related field.
• Minimum 3+ years of professional experience in machine learning engineering or applied ML.
• Strong proficiency in Python and popular ML/DL frameworks such as TensorFlow, PyTorch, or Scikit-learn.
• Solid understanding of machine learning algorithms, statistical modeling, and predictive analytics.
• Hands-on experience with data preprocessing, feature engineering, and pipeline building.
• Familiarity with SQL/NoSQL databases and data handling in large-scale systems.
• Experience with cloud platforms (AWS, GCP, Azure) and ML services for deployment.
• Strong problem-solving skills, with the ability to work independently and in collaborative team environments.

Preferred Skills (Good to Have)

• Exposure to Natural Language Processing (NLP), Computer Vision, or Reinforcement Learning.
• Experience in MLOps practices including CI/CD pipelines, model versioning, and monitoring tools.
• Familiarity with big data technologies like Spark, Hadoop, or Kafka.
• Knowledge of Docker, Kubernetes, or other containerization/orchestration tools.

Skills Required