<p><p><b>Job Description Machine Learning / Deep Learning Engineer</b><br/><br/><b>Location : </b> Gurugram (Work from Office)<br/><br/><b>Experience : </b> 26 years <br/><br/><b>Employment Type : </b> the Role : </b></p><p><p><b><br/></b></p>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.</p><p>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.</p><p><br/></p><p><b>Key Responsibilities : </b></p><p><p><b><br/></b></p>- Design, implement, and optimize ML/DL models for real-world applications (classification, regression, NLP, computer vision, etc.).<br/><br/></p><p>- Work with data pipelines : preprocessing, feature engineering, and exploratory data analysis (EDA).<br/><br/></p><p>- Deploy ML models on cloud environments (AWS Sagemaker, GCP Vertex AI, Azure ML, or similar).<br/><br/></p><p>- Build and maintain FastAPI endpoints for serving models and integrating with front-end and backend systems.<br/><br/></p><p>- Collaborate with cross-functional teams to define business problems and translate them into ML solutions.<br/><br/></p><p>- Optimize model performance, scalability, and monitoring in production.<br/><br/></p><p>- Stay updated with the latest trends in ML, DL, and cloud-native AI Skills & Qualifications : </b></p><p><br/></p><p>- Bachelors/Masters degree in Computer Science, Data Science, AI/ML, or related ML/DL Expertise : </b></p><p><b><br/></b></p>- Proficiency in Python and ML/DL libraries (TensorFlow, PyTorch, scikit-learn).<br/><br/></p><p>- Experience with model training, hyperparameter tuning, evaluation, and Knowledge : </b></p><p><br/></p><p>- Hands-on with at least one cloud platform (AWS, GCP, or Azure).</p><p><br/></p>- Familiarity with containerization (Docker) and orchestration (Kubernetes) is a Science Knowledge : </b></p><p><b><br/></b></p>- Strong in data preprocessing, feature engineering, and exploratory analysis.<br/><br/></p><p>- Understanding of SQL and NoSQL Development : </b></p><p><b> </b></p>- Experience with FastAPI (preferred) or Flask/Django REST for model deployment.<br/><br/></p><p>- Familiarity with CI/CD pipelines, version control (Git), and ML model lifecycle management Skills : </b></p><p><br/></p><p>- Knowledge of NLP (transformers, LLMs) or Computer Vision (CNNs, object detection).</p><p><br/></p>- Exposure to big data frameworks (Spark, Hadoop).<br/><br/></p><p>- Experience in deploying scalable AI solutions for production workloads.</p><br/></p> (ref:hirist.tech)