Senior Associate – Data Science & Machine Learning

About the job

Role: Senior Associate – Data Science & Machine Learning Experience: 5 to 8 Years Work Mode: Hybrid (3 days office per week) Location: Gurugram (GGN)/Bengaluru (BEN) Notice Period: Immediate to 2 weeks ONLY Employment Type: Full-Time About the Role We are seeking an experienced Data Science & Machine Learning Engineer who can design, build, and deploy advanced ML and AI-driven solutions. This role demands deep technical expertise in ML algorithms, deep learning architectures, LLMs, and model operationalization on cloud platforms. Key Responsibilities • Build predictive models using classification, regression, clustering, and time-series techniques. • Perform feature engineering, algorithm selection, hyperparameter tuning, and model evaluation. • Build deep learning models using PyTorch or TensorFlow (CNNs, RNNs, transformers). • Develop GenAI applications using embeddings, LLMs, prompt engineering, RAG pipelines, LangChain, LlamaIndex, HuggingFace models. • Design and implement end-to-end ML pipelines from ingestion to deployment. • Build scalable data pipelines and work with cloud-based ML platforms (AWS/GCP/Azure ML). • Deploy, monitor, and maintain ML models using MLOps tools and CI/CD workflows. • Work closely with product and engineering teams to integrate ML solutions. Must-Have Skills • Strong fundamentals: Statistics, Probability, Linear Algebra, Optimization • Machine Learning: • Classification, Regression, Clustering • Model evaluation (AUC, F1, Recall, ROC curves) • Cross-validation, bias-variance trade-off • Deep Learning: • CNNs, RNNs, Transformers • Hands-on PyTorch / TensorFlow • GenAI & NLP: • LLMs (GPT, LLaMA, Claude, etc.) • Embeddings, RAG, vector databases • Prompt engineering, model fine-tuning • Programming: • Python (NumPy, Pandas, Scikit-learn) • PyTorch/TensorFlow • SQL • MLOps: • CI/CD • Model deployment & monitoring • Lifecycle management • Version control (Git) and cloud ML platforms (AWS/GCP/Azure) Good to Have • Experience with Hugging Face models • Knowledge of Docker/Kubernetes • Exposure to reinforcement learning • Experience with A/B testing or experimentation frameworks Required Candidate Information(For screening – mandatory) • Total Experience • Relevant DS/ML Experience • Current CTC • Expected CTC • Notice Period ( Immediate – 2 weeks only ) • Current Location • Preferred Location • LinkedIn Profile URL How to Apply Send your updated CV to:

Requirements

• Statistics
• Probability
• Linear Algebra
• Optimization
• Classification
• Regression
• Clustering
• Deep Learning
• Python
• PyTorch
• TensorFlow
• MLOps

Preferred Technologies

• Statistics
• Probability
• Linear Algebra
• Optimization
• Classification
• Regression
• Clustering
• Deep Learning
• Python
• PyTorch
• TensorFlow
• MLOps