Artificial Intelligence Engineer

About Es Magico

Es Magico is an AI-first enterprise transformation organisation that goes beyond consulting to deliver scalable execution across industries like BFSI, Healthcare, Entertainment, and Education. With offices in Mumbai and Bengaluru, we focus on enhancing the human workforce by building bespoke AI employees across business functions—innovating swiftly, executing with trust.

We also collaborate with early-stage startups in their 0 → 1 journey as a venture builder, bringing AI-native products to life.

About the role

As an L3/L4 AI Engineer at Es Magico, you will work at the intersection of applied research and engineering execution. You will be responsible for independently designing, developing, and deploying AI/ML solutions that solve complex enterprise problems at scale. You will work closely with Product, Engineering, and Client teams to convert ambiguous requirements into production-grade AI systems.

Responsibilities:

• Own the design, development, and optimisation of ML/DL models for enterprise-grade applications.
• Explore, evaluate, and implement state-of-the-art algorithms across NLP, CV, and Predictive Modelling.
• Lead data preprocessing, feature engineering, and exploratory data analysis with an execution-first mindset.
• Develop robust proof-of-concepts as well as scalable AI pipelines and production-ready prototypes.
• Drive model evaluation, optimisation, hyperparameter tuning, and continuous performance monitoring.
• Work with cross-functional teams to define problem statements, technical feasibility, and success metrics.
• Write clean, modular, reproducible code with strong documentation across experiments and deployments.
• Provide mentorship to interns and junior ML engineers where required.

Tech Stack / Tools You’ll Use:

• Programming:

  Python

• ML/DL:

  TensorFlow, PyTorch, Scikit-learn

• NLP/CV:

  NLTK, spaCy, Transformers, OpenCV

• Data:

  Pandas, NumPy

• Cloud:

  Azure ML, Databricks (preferred)

• Version Control:

  Git, GitHub/GitLab

• Experiment Tracking:

  MLflow, Weights & Biases (preferred)

• CI/CD & Deployment:

  Docker, basic understanding of MLOps pipelines (good to have)



Requirements:

• Bachelor’s or Master’s degree in CS, Data Science, AI, or a related discipline.
• 2–4+ years of hands-on experience building and deploying ML/DL models.
• Strong understanding of ML fundamentals, optimisation techniques, data structures, and algorithms.
• Applied experience in deep learning (CNN, RNN, LSTMs, Transformers); experience with LLMs is an advantage.
• Ability to translate high-level business problems into structured ML solutions.
• Strong debugging, problem-solving skills, and a bias toward rapid experimentation and execution.
• Experience working in fast-paced, ambiguity-driven environments or early-stage products is a plus.