AIML Engineer

Position Summary

We are looking for a strong hands-on AI/ML Engineer with 4+ years of experience who can independently design, develop, train, evaluate, and deploy machine learning models from scratch. The ideal candidate should have strong fundamentals in ML/DL, excellent Python skills, and proven experience taking models from experimentation to production.

Key Responsibilities

• Design and develop AI/ML models from scratch based on business and technical requirements.
• Perform data collection, preprocessing, feature engineering, model selection, training, tuning and evaluation.
• Develop and optimize supervised and unsupervised machine learning models.
• Work on Deep Learning/NLP/GenAI use cases as applicable.
• Build complete ML pipelines from data preparation to model deployment and monitoring.
• Perform model experimentation and improve accuracy, performance, scalability and reliability.
• Apply statistical and machine-learning techniques to solve complex business problems.
• Conduct model validation, error analysis, A/B testing and performance benchmarking.
• Collaborate with Data Engineers, Software Engineers, Product Managers and business stakeholders.
• Productionize ML models through APIs, batch pipelines or real-time inference systems.
• Implement MLOps practices, including model versioning, experiment tracking, CI/CD and model monitoring.
• Stay current with emerging AI/ML techniques and evaluate their applicability to business problems.

Mandatory Technical Skills

• 4+ years of hands-on AI/ML development experience
• Strong Python programming skills.
• Strong understanding of:
  • Machine Learning algorithms
  • Statistics & Probability
  • Feature Engineering
  • Model Evaluation & Optimization
  • Regression & Classification
  • Clustering
  • Ensemble methods
• Hands-on experience with Scikit-learn, Pandas, NumPy.
• Strong experience with PyTorch and/or TensorFlow.
• Ability to build ML models from scratch, rather than only consuming pre-built APIs/models.
• Experience with model hyperparameter tuning and performance optimization.
• Strong SQL and data-handling skills.
• Experience developing production-ready ML solutions.

Good to Have

• NLP / LLM / Generative AI experience.
• Experience with Transformers, Hugging Face, LangChain or similar frameworks.
• Computer Vision experience.
• Experience with AWS / Azure / GCP.
• Docker and Kubernetes.
• MLflow, Kubeflow or other MLOps platforms.
• REST API development using FastAPI/Flask.
• Experience with Spark/PySpark.
• Experience deploying models at scale.