Machine learning Engineer
1 day ago
This role is for one of Weekday's clients
Min Experience: 4 years
Location: Bangalore
JobType: full-time
Requirements
We are seeking an experienced and innovative Machine Learning Engineer to join our growing data science and AI team. In this role, you will design, build, and deploy scalable ML models and pipelines that power intelligent decision-making across our products and platforms. You'll work closely with data scientists, software engineers, and product teams to transform complex data into actionable insights and automated solutions.
As a Machine Learning Engineer, you'll play a key role in operationalizing models, optimizing performance, and ensuring reliability in production environments. You'll also explore new algorithms, experiment with modern ML techniques, and help shape the strategic direction of our AI initiatives.
Key Responsibilities- Design, develop, and deploy machine learning models for predictive analytics, classification, recommendation, and anomaly detection.
- Build scalable data pipelines for feature extraction, model training, and evaluation using modern ML frameworks and tools.
- Collaborate with data scientists to convert research prototypes into production-ready models.
- Implement end-to-end ML systems, from data ingestion and preprocessing to model deployment and monitoring.
- Continuously evaluate and improve model performance through tuning, retraining, and data-driven optimization.
- Work with software and platform teams to integrate ML outputs into core applications and APIs.
- Develop automated CI/CD workflows for ML experiments and production deployments.
- Ensure data and model governance, including version control, reproducibility, and explainability.
- Stay up to date with emerging trends in machine learning, deep learning, and MLOps, bringing innovative ideas to the team.
- Partner with stakeholders to identify business challenges that can be solved with ML-driven approaches.
- Bachelor's or Master's degree in Computer Science, Data Science, Mathematics, or related field.
- 4+ years of hands-on experience in building and deploying machine learning models in real-world applications.
- Strong knowledge of machine learning algorithms, statistical modeling, and data preprocessing techniques.
- Proficiency in Python and experience with ML frameworks such as TensorFlow, PyTorch, Scikit-learn, or XGBoost.
- Expertise in data manipulation and analysis using Pandas, NumPy, and SQL.
- Experience with end-to-end ML pipelines, including data engineering, model training, testing, and deployment.
- Working knowledge of cloud platforms such as AWS, GCP, or Azure for ML workloads.
- Familiarity with containerization and orchestration tools like Docker and Kubernetes is a plus.
- Strong analytical and problem-solving skills with attention to scalability and performance.
- Excellent communication skills and ability to collaborate across technical and business teams.
- Experience in MLOps tools like MLflow, Kubeflow, Airflow, or SageMaker.
- Understanding of deep learning architectures for NLP or computer vision.
- Exposure to feature store management, model versioning, and monitoring frameworks.
- Passion for continuous learning and applying ML to real-world business problems.
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