About the Opportunity
Join a fast-growing tech consultancy driving AI innovation for enterprise clients across India. We build and deploy scalable machine learning systems that solve real-world business challenges—from predictive analytics and NLP pipelines to computer vision and recommendation engines. You’ll work directly with global brands, deploying production-grade ML models using modern cloud infrastructure and MLOps best practices.
Role & Responsibilities
- Design, develop, and productionize ML models for high-impact business use cases spanning classification, regression, clustering, and deep learning.
- Build and optimize end-to-end ML pipelines—from data preprocessing and feature engineering to model training, hyperparameter tuning, and inference deployment.
- Deploy models on cloud platforms (AWS/Azure/GCP) using containerization (Docker/K8s), serverless functions, and CI/CD workflows.
- Collaborate with data engineers to ensure clean,
scalable data pipelines and with product teams to translate business KPIs into ML-driven outcomes.
- Monitor model performance in production, implement drift detection, retraining workflows, and ML observability dashboards.
- Mentor junior engineers and contribute to internal AI/ML engineering standards, code reviews, and architecture design sessions.
Skills & Qualifications
Must-Have
- Python
- Scikit-learn
- TensorFlow
- PyTorch
- NumPy
- Pandas
- MLflow
- Amazon SageMaker
Preferred
- ML Ops tools (Kubeflow, Airflow)
- Model monitoring platforms (Arize, Evidently)
- Experience with LLM fine-tuning or RAG pipelines
Benefits & Culture Highlights
- Work on high-visibility AI projects for Fortune 500 clients across finance, retail, and healthcare.
- On-site hybrid model with flexible schedule and modern office infrastructure in major Indian metro cities.
- Access to internal AI upskilling programs, conference sponsorships, and performance-linked bonuses.