AI/ML Engineer

This role is for one of Weekday's clients

Min Experience: 2 years

Location: gurugram, NCR, Delhi, NOIDA, Uttar Pradesh

JobType: full-time

About the Role:

AI/ML Engineer

You'll collaborate with cross-functional teams including data scientists, software engineers, and product managers to build scalable and robust ML-powered applications.

Key Responsibilities:

Model Development & Deployment

• Design, build, and train machine learning models to support core product features.
• Experiment with supervised, unsupervised, and deep learning algorithms to solve business challenges.
• Deploy models into production environments and monitor their performance.

Data Handling & Feature Engineering

• Collect, clean, preprocess, and analyze large volumes of structured and unstructured data.
• Engineer features that enhance model performance and align with product requirements.
• Ensure data quality and consistency across the pipeline.

Model Optimization

• Evaluate model performance using relevant metrics (precision, recall, F1-score, ROC-AUC, etc.).
• Optimize models for speed and accuracy using hyperparameter tuning, ensemble methods, or transfer learning.

Collaboration & Integration

• Collaborate with backend and frontend teams to integrate AI/ML capabilities into products.
• Build APIs and services that expose ML models for consumption across applications.
• Work closely with data engineers and DevOps to deploy and scale ML pipelines.

Research & Innovation

• Stay updated on the latest trends, tools, and frameworks in AI/ML.
• Prototype and test innovative AI solutions, including NLP, computer vision, recommendation systems, or time series forecasting.
• Document methodologies, findings, and technical processes clearly.

Skills & Qualifications:

• Bachelor's or Master's degree in Computer Science, Data Science, Machine Learning, or related field.

• 2+ years of hands-on experience

  in AI/ML model development and deployment.
• Strong knowledge of

  Python

  and ML libraries such as

  scikit-learn, TensorFlow, Keras, PyTorch, XGBoost,

  or similar.
• Experience with data manipulation tools like

  Pandas

  ,

  NumPy

  , and visualization libraries such as

  Matplotlib

  or

  Seaborn

  .
• Understanding of ML lifecycle, including data preprocessing, model building, evaluation, and deployment.
• Familiarity with cloud platforms (AWS, GCP, Azure) and container technologies like Docker is a plus.
• Knowledge of REST APIs and integration of ML models with applications.
• Excellent problem-solving and analytical skills.
• Strong communication skills and ability to explain complex ML concepts to non-technical stakeholders.

Preferred (Nice to Have):

• Experience with

  Natural Language Processing (NLP)

  ,

  Computer Vision

  , or

  Reinforcement Learning

  .
• Exposure to

  MLOps

  , model monitoring, or CI/CD pipelines.
• Familiarity with data versioning tools like

  DVC

  ,

  MLflow

  , or

  Kubeflow

  .