Senior Associate – Data Science & Machine Learning

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: