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Machine Learning Engineer
2 weeks ago
Job Description Machine Learning / Deep Learning Engineer
Location :
Gurugram (Work from Office)
Experience :
26 years
Employment Type :
the Role :
We are seeking a highly motivated Machine Learning / Deep Learning Engineer who can design, develop, and deploy end-to-end AI solutions. The ideal candidate will have strong expertise in ML/DL, hands-on experience with cloud platforms (AWS / GCP / Azure), solid understanding of data science pipelines, and proven ability to build APIs using FastAPI for scalable deployment.
This is a client-facing, product-focused role where youll collaborate with data scientists, backend engineers, and business teams to bring AI models into production.
Key Responsibilities
- Design, implement, and optimize ML/DL models for real-world applications (classification, regression, NLP, computer vision, etc.).
- Work with data pipelines : preprocessing, feature engineering, and exploratory data analysis (EDA).
- Deploy ML models on cloud environments (AWS Sagemaker, GCP Vertex AI, Azure ML, or similar).
- Build and maintain FastAPI endpoints for serving models and integrating with front-end and backend systems.
- Collaborate with cross-functional teams to define business problems and translate them into ML solutions.
- Optimize model performance, scalability, and monitoring in production.
- Stay updated with the latest trends in ML, DL, and cloud-native AI Skills & Qualifications :
- Bachelors/Masters degree in Computer Science, Data Science, AI/ML, or related ML/DL Expertise :
- Proficiency in Python and ML/DL libraries (TensorFlow, PyTorch, scikit-learn).
- Experience with model training, hyperparameter tuning, evaluation, and Knowledge :
- Hands-on with at least one cloud platform (AWS, GCP, or Azure).
- Familiarity with containerization (Docker) and orchestration (Kubernetes) is a Science Knowledge :
- Strong in data preprocessing, feature engineering, and exploratory analysis.
- Understanding of SQL and NoSQL Development :
- Experience with FastAPI (preferred) or Flask/Django REST for model deployment.
- Familiarity with CI/CD pipelines, version control (Git), and ML model lifecycle management Skills :
- Knowledge of NLP (transformers, LLMs) or Computer Vision (CNNs, object detection).
- Exposure to big data frameworks (Spark, Hadoop).
- Experience in deploying scalable AI solutions for production workloads.
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