Senior Machine Learning Engineer

Job Summary

We are seeking an experienced Senior Machine Learning Engineer to join our team. The successful candidate will be responsible for designing, developing, and deploying scalable machine learning models for real-world business problems using structured and unstructured data.

Responsibilities

• Design, develop, and deploy scalable machine learning models for real-world business problems using structured and unstructured data.
• Analyze large datasets using PySpark and other distributed computing frameworks to extract insights and prepare features for ML pipelines.
• Apply a wide range of statistical, machine learning, and deep learning techniques, including but not limited to regression, classification, clustering, time-series forecasting, and NLP.
• Own end-to-end ML pipelines from data ingestion, preprocessing, training, validation, tuning, and deployment.
• Utilize Amazon SageMaker or similar platforms for building, training, and deploying models in a production-grade environment.
• Collaborate closely with data engineers, data scientists, and product teams to integrate models with business workflows.
• Monitor and improve model performance, scalability, and reliability in production.
• Contribute to setting up and maintaining the ML environment and tooling (including environment configuration, CI/CD pipelines for ML, model versioning, etc.).

Requirements

• 7+ years of experience in machine learning, data science, or related fields.
• Strong programming skills in Python with experience in ML libraries (e.g., scikit-learn, XGBoost, TensorFlow, PyTorch).
• Hands-on experience with PySpark for big data processing and model development.
• Solid understanding of statistical analysis, probability, hypothesis testing, and experimental design.
• Experience with Amazon SageMaker (or similar cloud-based ML platforms).
• Strong knowledge of ML Ops practices including version control, model monitoring, and retraining strategies.
• Familiarity with containerization (Docker) and CI/CD practices for ML projects is a plus.
• Excellent communication skills and the ability to clearly explain complex concepts to non-technical stakeholders.
• Master's or Ph.D. in Computer Science, Statistics, Mathematics, or a related quantitative discipline.
• Experience with workflow orchestration tools (e.g., Airflow, Kubeflow).
• Prior experience in domains like Manufacturing, finance, healthcare, or e-commerce is a plus.

Qualifications

Master's or Ph.D. in Computer Science, Statistics, Mathematics, or a related quantitative discipline.

Benefits

Competitive salary, comprehensive benefits package, professional development opportunities, and a dynamic work environment.

Pay

$150,000 - $200,000 annually

Schedule

Full-time, Monday through Friday, 9 AM to 5 PM