AI/ML Engineer - Python

Job Title : AI/ML Engineer Location : Gurugram Experience : 5 Years Job Type : Full-time Key Responsibilities : 1. Model Development & Optimization : Design & Implementation : - Architect and build end-to-end machine learning solutions across domains like predictive analytics, anomaly detection, computer vision, and natural language processing. - Employ advanced methodologies including Deep Learning (CNNs, RNNs), Reinforcement Learning, and Generative Models (GANs). Optimization : - Optimize model performance through hyperparameter tuning techniques such as Grid Search, Bayesian Optimization, and Neural Architecture Search. - Balance model accuracy with real-time inference requirements for production readiness. 2. Advanced Data Engineering & Integration : Data Pipeline Development : - Create scalable ETL pipelines using Pandas, NumPy, and PySpark to process large-scale and streaming data from various sources (e.g., satellite imagery, IoT devices). - Integrate structured and unstructured data from APIs, databases, and big data platforms (Hadoop, Kafka). Data Preprocessing : - Perform data cleansing, transformation, and feature engineering to ensure model-ready datasets. 3. Research & Innovation Algorithm Research : - Stay updated and experiment with state-of-the-art ML techniques such as Transfer Learning, Transformer models, and AutoML. - Innovate and adapt algorithms for specialized domains like geospatial analysis, environmental modeling, and cybersecurity. Prototyping & Experimentation : - Rapidly build and test proof-of-concept models to validate innovative approaches. 4. Deployment, MLOps & Performance Monitoring : Model Deployment : - Deploy ML models using Docker and Kubernetes in cloud environments (AWS, GCP, Azure). - Use model serving tools such as TensorFlow Serving, ONNX, or TorchServe for scalable inference. MLOps & Lifecycle Management : - Set up CI/CD pipelines for streamlined model updates and versioning. - Implement monitoring and alerting systems using Prometheus and Grafana for performance tracking and automated retraining triggers. 5. Collaboration & Leadership : Cross-Functional Collaboration : - Work closely with data engineers, developers, domain experts, and product teams to integrate AI solutions into business products. Mentorship & Code Quality : - Lead and mentor junior team members, enforce coding standards, and promote knowledge sharing through documentation and code reviews. Recommended Tech Stack : - Backend : Python (FastAPI, Django) - AI/ML : PyTorch, Hugging Face Transformers, scikit-learn - Data Engineering : Apache Kafka, Spark, NiFi - Database : PostgreSQL with TimescaleDB - DevOps : Docker, Kubernetes, GitLab CI/CD, Prometheus, Grafana - Media Processing : OpenCV, FFmpeg, Tesseract OCR, Wav2Vec2 Required Skills & Qualifications : - Experience : 5 years in ML/AI, with a proven track record of building and deploying production-grade models. - Programming : Strong Python skills and proficiency with PyTorch, TensorFlow, scikit-learn. - NLP : Experience using Hugging Face Transformers. - Data Engineering : Expertise in Pandas, NumPy, PySpark; familiar with big data platforms and streaming architectures. - Deployment : Experience with Docker, Kubernetes, and CI/CD practices. - Cloud & Serving : Hands-on experience with cloud platforms and model serving frameworks. - Research Orientation : Comfortable exploring new algorithms and techniques to improve model performance. - Optimization : Solid understanding of evaluation metrics, model tuning, and inference efficiency. Soft Skills : - Excellent analytical and problem-solving capabilities. - Strong communication and interpersonal skills. - Experience in mentoring and working in agile, cross-functional teams. - Self-driven, curious, and able to work in a fast-paced environment. Education : - Bachelor's or Master's in Computer Science, Data Science, Machine Learning, or related field from a reputed institution. (ref:hirist.tech)

Location: in, IN

Posted Date: 5/1/2025