Artificial Intelligence Engineer

About the Role

AI/ML Engineer

Key Responsibilities

• Model Development & Deployment

• Design, build, train, and fine-tune machine learning and deep learning models.
• Deploy models into production using MLOps frameworks and cloud platforms.

• Data Processing & Feature Engineering

• Clean, preprocess, and transform structured and unstructured data.
• Implement feature selection, extraction, and dimensionality reduction techniques.

• Algorithm Optimization

• Evaluate model performance using appropriate metrics and improve accuracy, efficiency, and scalability.

• Integration & Automation

• Collaborate with engineering teams to integrate AI models into applications and services.
• Automate pipelines for model retraining and deployment.

• Research & Innovation

• Stay updated with the latest advancements in AI/ML, NLP, and computer vision.
• Experiment with new algorithms, architectures, and frameworks.

Required Skills & Qualifications

• Education

• Bachelor’s or Master’s in Computer Science, Data Science, AI, or related field.

• Technical Skills

• Strong programming skills in

  Python

  (NumPy, Pandas, Scikit-learn).
• Proficiency in deep learning frameworks (

  TensorFlow

  ,

  PyTorch

  ,

  Keras

  ).
• Experience with

  NLP

  ,

  Computer Vision

  , or

  Recommendation Systems

  .
• Knowledge of cloud platforms (

  AWS

  ,

  Azure

  ,

  GCP

  ) for AI deployments.
• Hands-on with MLOps tools (

  Docker

  ,

  Kubernetes

  ,

  GitHub Actions

  ,

  MLflow

  ,

  Kubeflow

  ).
• Familiarity with big data tools (

  Spark

  ,

  Hadoop

  ) is a plus.

• Soft Skills

• Strong problem-solving and analytical skills.
• Effective communication for cross-functional collaboration.
• Ability to work independently and in agile teams.

Preferred Experience

• Experience with

  transformer architectures

  (e.g., BERT, GPT, LLaMA).
• Familiarity with

  LangChain

  ,

  Vector Databases

  , and

  Generative AI

  .
• Exposure to

  reinforcement learning

  and

  time series forecasting

  .

Perks & Benefits

• Competitive salary and performance bonuses.
• Flexible working hours and remote work options.
• Learning & development budget for certifications and conferences.

if interested please share the profiles to this vivekraj.d@hepl.com