Machine Learning Engineer

Job Description

Job Summary: We are looking for highly motivated and analytical Machine Learning Engineers with 1–3 years of experience in building scalable, production-ready AI/ML models. This role involves working on complex business problems using advanced ML/DL techniques across domains such as Natural Language Processing (NLP), Computer Vision, Time Series Forecasting, and Generative AI. You will be responsible for end-to-end model development, deployment, and performance tracking while collaborating with cross-functional teams including data engineering, DevOps, and product. Location: Noida / Gurugram / Indore / Bengaluru / Pune / Hyderabad Experience: 1–3 Years Education: BE / B.Tech / M.Tech / MCA / M.Com Key Responsibilities: Model Development & Experimentation Design and build machine learning models for NLP, computer vision, and time series prediction using supervised, unsupervised, and deep learning techniques. Conduct experiments to improve model performance via architectural modifications, hyperparameter tuning, and feature selection. Apply statistical analysis to validate and interpret model results. Evaluate models using appropriate metrics (e.g., accuracy, precision, recall, F1-score, AUC-ROC). Data Handling & Feature Engineering Process large structured and unstructured datasets using Python, Pandas, and DataFrame APIs. Perform feature extraction, transformation, and selection tailored to specific ML problems. Implement data augmentation and enrichment techniques to enhance training quality. Model Deployment & Productionization Deploy trained models to production environments using cloud platforms such as AWS (especially SageMaker). Containerize models using Docker and orchestrate deployments with Kubernetes. Implement monitoring, logging, and automated retraining pipelines for model health tracking. Collaboration & Innovation Collaborate with data engineers and architects to ensure smooth data flow and infrastructure alignment. Explore and adopt cutting-edge AI/ML methodologies and GenAI frameworks (e.g., LangChain, GPT-3). Contribute to documentation, versioning, and knowledge-sharing across teams. Drive innovation and continuous improvement in AI/ML delivery and engineering practices. Mandatory Technical Skills: Languages & Tools: Python (Pandas, NumPy, Scikit-learn, TensorFlow/PyTorch) Model Development: Deep Learning, NLP, Time Series, Computer Vision Cloud Platforms: AWS (especially SageMaker) Model Deployment: Docker, Kubernetes, REST APIs ML Ops: Model monitoring, performance logging, CI/CD Frameworks: LangChain (for GenAI), Transformers, Hugging Face Preferred / Good to Have: Experience with Foundation Model tuning and prompt engineering Hands-on with Generative AI (GPT-3/4, OpenAI APIs, LangChain integrations) Certifications: AWS Certified Machine Learning – Specialty Experience with version control (Git), and experiment tracking tools (MLflow, Weights & Biases) Soft Skills: Excellent communication and presentation abilities Strong analytical and problem-solving mindset Ability to work in collaborative, fast-paced environments Curiosity to learn emerging technologies and apply them to real-world problems Show more Show less