Chennai, Tamil Nadu, India
Space Exploration & Research, Information Technology
Full-Time
Whitefield Careers
Overview
Sr. Data Scientist JD.docx
Job Title: Senior Data Scientist | Machine Learning Engineer (MLE)
Job Location: [Mohali / Pune]
Experience: 4+ years
Skill Sets
Expertise in ML/DL, model lifecycle management, and MLOps (MLflow, Kubeflow) Proficiency in Python, TensorFlow, PyTorch, Scikit-learn, and Hugging Face models Strong experience in NLP, fine-tuning transformer models, and dataset preparation Hands-on with cloud platforms (AWS, GCP, Azure) and scalable ML deployment
(Sagemaker, Vertex AI) Experience in containerization (Docker, Kubernetes) and CI/CD pipelines Knowledge of distributed computing (Spark, Ray), vector databases (FAISS, Milvus),
and model optimization (quantization, pruning) Familiarity with model evaluation, hyperparameter tuning, and model monitoring for drift
detection
Roles & Responsibilities
Design and implement end-to-end ML pipelines from data ingestion to production Develop, fine-tune, and optimize ML models, ensuring high performance and scalability Compare and evaluate models using key metrics (F1-score, AUC-ROC, BLEU etc) Automate model retraining, monitoring, and drift detection Collaborate with engineering teams for seamless ML integration Mentor junior team members and enforce best practices
Job Title: Senior Data Scientist | Machine Learning Engineer (MLE)
Job Location: [Mohali / Pune]
Experience: 4+ years
Skill Sets
Expertise in ML/DL, model lifecycle management, and MLOps (MLflow, Kubeflow) Proficiency in Python, TensorFlow, PyTorch, Scikit-learn, and Hugging Face models Strong experience in NLP, fine-tuning transformer models, and dataset preparation Hands-on with cloud platforms (AWS, GCP, Azure) and scalable ML deployment
(Sagemaker, Vertex AI) Experience in containerization (Docker, Kubernetes) and CI/CD pipelines Knowledge of distributed computing (Spark, Ray), vector databases (FAISS, Milvus),
and model optimization (quantization, pruning) Familiarity with model evaluation, hyperparameter tuning, and model monitoring for drift
detection
Roles & Responsibilities
Design and implement end-to-end ML pipelines from data ingestion to production Develop, fine-tune, and optimize ML models, ensuring high performance and scalability Compare and evaluate models using key metrics (F1-score, AUC-ROC, BLEU etc) Automate model retraining, monitoring, and drift detection Collaborate with engineering teams for seamless ML integration Mentor junior team members and enforce best practices
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