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Machine Learning Engineer
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Gurugram, India Leegality Full timeThis is a remote position. About Leegality: We're India's very first Document Infrastructure Platform. Our mission? To completely transform how businesses handle paperwork, contracts, and getting digital consent. We make critical paperwork flows faster, way more innovative, and completely compliant for Indian businesses. Over 2,000 companies, from huge...
Machine Learning Engineer
4 weeks ago
Key Responsibilities :- Design, build, and optimize machine learning models for classification, regression, NLP, computer vision, recommendation systems, or generative AI use cases. - Perform data preprocessing, feature engineering, and model selection to deliver high-quality outcomes. Implement end-to-end machine learning pipelines from data ingestion to model deployment. - Develop NLP models for text classification, NER, embeddings, document understanding, and chatbot/agentic workflows. - Work with modern AI frameworks for LLM fine-tuning, prompt engineering, RAG, and generative AI solutions. - Deploy ML models in production environments using CI/CD and MLOps platforms. - Monitor model performance, drift, and accuracy; implement retraining or optimization as required. - Work with Docker, Kubernetes, Airflow, MLflow, or cloud-native ML services. - Work with data engineers to improve data pipelines, data quality, and real-time data processing. - Manage structured and unstructured data sources across cloud ecosystems. - Stay updated with the latest advancements in machine learning, deep learning, and generative AI. - Evaluate new models, algorithms, and techniques; contribute to experimentation and POCs. - Collaborate with product managers, software engineers, and domain experts to deliver AI-driven features. - Translate business problems into ML/AI solutions with measurable impact. Required Skills & Qualifications :- Bachelors or Masters degree in Computer Science, Data Science, AI/ML, or related field. 35 years of hands-on experience in Machine Learning, Deep Learning, and AI solution engineering. - Strong proficiency in Python and ML libraries such as scikit-learn, TensorFlow, PyTorch, Hugging Face Transformers, etc. - Experience building and deploying models in production environments. - Strong understanding of ML algorithms, feature engineering, model validation, and performance evaluation. - Experience with NLP techniques (text analytics, embeddings, transformers, document intelligence). Familiarity with MLOps tools like MLflow, Kubeflow, Airflow, or equivalent. - Experience with cloud platforms such as AWS, Azure, or GCP. - Strong understanding of data structures, algorithms, and software engineering practices. Preferred Skills : (Nice to Have) - Experience with Generative AI (LLMs, diffusion models, prompt engineering). - Knowledge of vector databases (FAISS, Pinecone, Chroma). - Experience with RAG pipelines and fine-tuning LLMs. - Familiarity with big data tools : Spark, Databricks, Kafka. - Experience in domain-specific solutions (Healthcare, Finance, Retail, etc.). (ref:hirist.tech)
