Python Developer - AI/ML

Location: On site

Arcitech.ai

Your Responsibilities

• AI/ML Engineering

• Develop, train, and optimize ML models using

  PyTorch/TensorFlow/Keras

  .
• Build production-ready pipelines for

  data preprocessing, feature engineering, and model deployment

  .
• Collaborate with data scientists to convert prototypes into

  scalable, production-grade AI systems

  .
• Integrate

  NLP, Computer Vision, and Recommendation Systems

  into customer-facing applications.
• Leverage

  transformer-based architectures (BERT, GPT, etc.)

  for real-world AI applications.

• Backend & Systems Development

• Design, develop, and maintain robust

  Python microservices

  with

  REST/GraphQL APIs

  .
• Implement

  real-time communication

  with Django Channels/WebSockets.
• Containerize AI services with

  Docker

  and deploy on

  Kubernetes (EKS/GKE/AKS)

  .
• Configure and manage

  AWS (EC2, S3, RDS, SageMaker, CloudWatch)

  for AI workloads.

• Reliability & Automation

• Develop background task queues with

  Celery

  , ensuring smart retries and monitoring.
• Implement

  CI/CD pipelines

  for automated model training, testing, and deployment.
• Write

  automated unit & integration tests

  (pytest/unittest) with 80% coverage.

• Collaboration

• Contribute to

  MLOps best practices

  and mentor peers in AI/ML integration.
• Participate in

  tech talks, code reviews, and AI learning sessions

  within the team.

• Bachelors or Master’s degree in

  Computer Science, AI/ML, or related field

  .
• 2–5 years of experience in

  Python development

  with a focus on AI/ML.
• Strong hands-on experience with

  NumPy, Pandas, and Scikit-learn

  .
• Proficiency with at least one deep learning framework (

  PyTorch, TensorFlow, Keras

  ).
• Experience deploying ML models into

  production systems

  .
• Solid understanding of

  REST/GraphQL APIs

  and cloud platforms (AWS/Azure/GCP).
• Familiarity with

  Git workflows, testing frameworks, and CI/CD practices

  .

Nice to Have

• Experience with

  LLMs, RAG (Retrieval-Augmented Generation), or Generative AI systems

  .
• Knowledge of

  data pipelines

  (Airflow, Prefect, Dagster).
• Exposure to

  statistics, optimization techniques, and applied mathematics

  .
• Contributions to

  AI/ML open-source projects

  .
• Familiarity with

  model monitoring and drift detection

  in production.

Why Join Us

• Competitive compensation and benefits
• Work on

  cutting-edge AI/ML applications

  with global impact
• A collaborative, innovation-driven work culture
• Opportunities to

  grow into AI leadership roles