AI/ML Developer (Lateral Hire)

Role Overview
We are seeking experienced AI/ML Developers to join our growing team. The ideal candidate will have hands-on experience delivering AI/ML projects end-to-end, a strong foundation in machine learning concepts, and a recognized AI/ML certification from a reputed institution. This role demands ownership of model development, deployment, and continuous improvement of AI/ML solutions in a collaborative engineering environment.
Experience Required

• Minimum 2–4 years of professional experience in AI/ML development.
• Demonstrable contribution to at least 3 AI/ML projects (production, client, or substantial proof-of-concept work). Candidates must be prepared to discuss architecture, dataset, modeling choices, evaluation, and outcomes for each project.
• Mandatory completion of an AI/ML certification from a recognized institution — for example, the IIT Delhi Generative AI & Automation Training Program (or an equivalent program from IIT/IISc/IIIT, Stanford, DeepLearning.AI, Google, AWS, or Microsoft). Certificate must be produced at the time of interview.
  

Key Responsibilities

• Design, develop, train, and deploy machine learning and deep learning models to solve real business problems.
• Own the full ML lifecycle: data ingestion, preprocessing, feature engineering, model training, evaluation, deployment, and monitoring.
• Build and maintain reusable ML pipelines and reproducible experimentation workflows.
• Collaborate with data engineers, product managers, and software engineers to integrate ML models into production systems via APIs and services.
• Optimize models for accuracy, latency, scalability, and cost.
• Conduct code reviews, write unit tests, and follow engineering best practices including version control and CI/CD.
• Stay current with developments in AI/ML and contribute to internal knowledge sharing.
  

Required Skills And Qualifications

• Bachelors degree in AI/ML, Data Science, Computer Science, or a related quantitative discipline is MUST.
• Strong proficiency in Python programming, including object-oriented programming and writing production-grade code.
• Solid grasp of Machine Learning concepts: supervised/unsupervised learning, bias-variance trade-off, overfitting/underfitting, regularization, model evaluation, and hyperparameter tuning.
• Hands-on experience with at least two ML/DL libraries: scikit-learn, TensorFlow, Keras, or PyTorch.
• Practical experience with data preprocessing techniques: normalization, encoding, handling missing values, outlier detection, and feature engineering.
• Working knowledge of core algorithms: linear/logistic regression, decision trees, random forests, gradient boosting, clustering, and neural networks.
• Proficient in SQL and experience working with relational databases.
• Hands-on experience with Git and collaborative version-control workflows (branching, pull requests, code reviews).
• Experience deploying ML models to production using REST APIs (Flask/FastAPI) or similar frameworks.
• Ability to write clean, readable, modular, and well-documented code.
• Strong communication skills and the ability to collaborate effectively in cross-functional teams.
  

Project Portfolio (Mandatory)
Candidates must showcase a minimum of 3 AI/ML projects with the following details:

• Problem statement and business context.
• Dataset details, preprocessing steps, and feature engineering approach.
• Models evaluated, final model selected, and rationale.
• Evaluation metrics and quantitative results.
• Deployment approach (if applicable) and lessons learned.
• GitHub links, Kaggle notebooks, or production references are strongly preferred.
  

Certification Requirement (Mandatory)
Candidates must hold a completed AI/ML certification from a recognized institution. Acceptable examples include, but are not limited to:

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• IIT Delhi — Generative AI & Automation Training Program (preferred).
• Equivalent AI/ML programs from IITs, IISc, IIITs, or other reputed Indian institutes.
• Globally recognized programs from Stanford Online, DeepLearning.AI, MIT, Google, AWS, or Microsoft.
• A copy of the certificate must be furnished at the time of the interview.
  

Nice-to-Have

• Hands-on experience with cloud platforms (AWS, GCP, or Azure) — especially with managed ML services such as SageMaker, Vertex AI, or Azure ML.
• Exposure to MLOps tools: MLflow, Airflow, Kubeflow, DVC, or Weights & Biases.
• Experience in specialized domains: NLP (transformers, LLMs, RAG), Computer Vision (CNNs, object detection), or Time Series Forecasting.
• Working knowledge of Generative AI, Large Language Models, prompt engineering, and frameworks like LangChain or LlamaIndex.
• Familiarity with Docker, Kubernetes, and CI/CD pipelines.
• Comfort with Jupyter Notebooks, Google Colab, and modern experiment-tracking tools.
• Participation in Kaggle competitions, AI hackathons, open-source contributions, or published research papers.
  

What We Offer

• Opportunity to work on impactful AI/ML projects across diverse business domains.
• A collaborative, learning-oriented engineering culture.
• Access to modern tools, cloud infrastructure, and continuous upskilling opportunities.
• Competitive compensation and growth path.
  

Panel - Phani