Machine Learning Engineer

2 weeks ago

Gurugram Gurugram India SWITS DIGITAL Private Limited Full time

Job Description

Job Title: Machine Learning Engineer

Experience Required: 5+ years

Location:

Job Summary

We are seeking a skilled Machine Learning Engineer to design, build, deploy, and maintain scalable ML solutions. The ideal candidate will have strong hands-on experience in building end-to-end ML pipelines, deploying models into production, and setting up CI/CD workflows. You will collaborate with data scientists, DevOps, and product teams to deliver high-quality ML solutions with robust monitoring and performance tracking.

Key Responsibilities

- Build and manage end-to-end ML pipelines (data ingestion preprocessing model training evaluation deployment monitoring).
- Deploy ML models using Azure ML Endpoints, Docker, FastAPI, or Flask.
- Implement CI/CD pipelines for ML workflows using Azure DevOps, GitHub Actions, or Jenkins.
- Monitor and log ML models in production using Azure Monitor, Application Insights, or custom logging frameworks.
- Ensure scalability, reliability, and security of ML systems in production.
- Collaborate with cross-functional teams to integrate ML models into business applications.
- Troubleshoot, optimize, and fine-tune ML models and infrastructure.

Required Skills & Qualifications

- 5+ years of experience in Machine Learning / MLOps / Data Engineering.
- Strong knowledge of Python and ML frameworks (e.g., scikit-learn, TensorFlow, PyTorch).
- Hands-on experience with end-to-end ML pipelines including data preprocessing, training, and deployment.
- Proficiency in containerization and deployment tools (Docker, FastAPI, Flask).
- Experience with Azure ML (preferred), AWS Sagemaker, or GCP Vertex AI.
- Strong understanding of CI/CD tools (Azure DevOps, GitHub Actions, Jenkins).
- Familiarity with monitoring tools (Azure Monitor, Application Insights, Prometheus, Grafana).
- Solid understanding of software engineering best practices (version control, testing, code reviews).
- Bachelor's/Master's degree in Computer Science, Data Science, or related field.

Good To Have

- Experience with Kubernetes or container orchestration tools.
- Exposure to big data platforms (Spark, Databricks, Hadoop).
- Knowledge of feature stores, ML model registries, and model explainability.
- Familiarity with Agile/Scrum methodology.

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