AI/ML Engineer

Description

Summary: The AI/ML Engineer designs, develops, and deploys machine learning models and AI-driven solutions, collaborating with cross-functional teams to drive intelligent automation and data-driven decision-making. Highlights: 1. Design, build, and deploy ML models for diverse applications 2. Implement MLOps practices and CI/CD pipelines for ML 3. Experiment with cutting-edge models and modern AI strategies **Job Title:** AI/ML Engineer **Department:** IT Services /IT Infrastructure **Reports To:** IT Project Manager **Location:** Delhi NCR (Remote) ### **Job Overview:** The AI/ML Engineer plays a critical role in designing, developing, and deploying machine learning models and AI\-driven solutions to support strategic business initiatives. The role involves collaborating with cross\-functional teams, including software engineering, data analytics, product development, and business stakeholders, to drive intelligent automation, data\-driven decision\-making, and advanced analytics capabilities. The ideal candidate will have 3 to 5 years of experience in AI/ML model development, with a strong foundation in machine learning algorithms, data preprocessing, and deployment pipelines. Experience with Python, TensorFlow/PyTorch, and cloud\-based ML services is essential. ### **Responsibilities:** ### **1\. Model Development and Optimization** * Design, build, and deploy ML models for classification, regression, NLP, computer vision, or time\-series forecasting. * Select appropriate algorithms and techniques based on business needs and data characteristics. * Continuously monitor and improve model performance using metrics and feedback loops. ### **2\. Data Preparation and Feature Engineering** * Clean, preprocess, and transform structured and unstructured datasets for training and inference. * Engineer and select relevant features to improve model accuracy and generalizability. * Collaborate with data engineers to ensure data quality and accessibility. ### **3\. Model Deployment and MLOps** * Package and deploy models using tools like Docker, Flask/FastAPI, and Kubernetes. * Implement CI/CD pipelines for ML using platforms like MLflow, Airflow, or Kubeflow. * Monitor deployed models for drift, latency, and performance in production environments. ### **4\. AI Solutions and Use Case Implementation** * Work with business stakeholders to translate real\-world problems into AI/ML use cases. * Prototype and test AI\-driven solutions (e.g., recommendation engines, chatbots, fraud detection). * Contribute to proof\-of\-concept projects and assist in scaling successful models to production. ### **5\. Research and Innovation** * Stay updated with the latest research, frameworks, and tools in machine learning and AI. * Experiment with cutting\-edge models (e.g., LLMs, transformers, generative AI) and assess their viability. * Promote innovation by recommending and implementing modern AI strategies. ### **6\. Cross\-functional Collaboration** * Collaborate with software developers, DevOps, data analysts, and domain experts for end\-to\-end solution delivery. * Translate technical insights into business value through clear documentation and presentations. ### **7\. Documentation and Best Practices** * Maintain comprehensive documentation for models, experiments, and pipelines. * Ensure reproducibility, scalability, and compliance with data governance policies. ### **Requirements:** ### **Experience:** * 3–5 years of hands\-on experience in machine learning model development and deployment. * Proven track record of solving real\-world problems using supervised, unsupervised, or deep learning methods. ### **Technical Skills:** **Strong knowledge of:** * Python and ML libraries (scikit\-learn, pandas, NumPy, TensorFlow/PyTorch) * Model evaluation, hyperparameter tuning, and pipeline automation * REST APIs for model serving and integration **Familiarity with:** * MLOps tools (MLflow, Airflow, DVC, Docker, Kubernetes) * Cloud ML services (AWS SageMaker, Azure ML, GCP AI Platform) * NLP or computer vision frameworks (e.g., Hugging Face, OpenCV) ### **Soft Skills:** * Strong analytical and problem\-solving abilities. * Excellent communication skills, both verbal and written. * Ability to work independently and within cross\-functional teams. * Curiosity, adaptability, and willingness to learn continuously.