AI Architect

4 days ago

Udaipur, Rajasthan, India beBeeMachine Full time ₹ 9,00,000 - ₹ 11,40,000

We are seeking a talented Machine Learning Engineer to join our team.

Job Description:

The ideal candidate will have a strong background in machine learning and software development, with experience in building scalable, distributed systems. They will be responsible for developing and maintaining backend architecture, implementing machine learning algorithms, ensuring efficient performance, and collaborating with front-end developers to integrate user-facing elements.

Key Responsibilities:
  • Build robust backend systems & APIs to deploy and scale ML solutions.
  • Work with cloud-native infrastructure (AWS) to design cost-efficient, high-availability ML pipelines and scalable cloud-supported backend solutions.
  • Implement ML lifecycle workflows — from experiment tracking (MLflow/Kubeflow/DVC) to orchestration (Airflow/Prefect).
  • Contribute to end-to-end product development: data ingestion, preprocessing, model serving, monitoring and continuous improvement.
  • Collaborate with cross-functional teams in a startup fast-paced environment.
  • Design backend APIs to support AI-driven process optimization and NLP-powered automations.
Requirements:

To be successful in this role, you will need:

  • Bachelor's / Master's degree in CS, Data Science, AI/ML
  • 1-3 years of experience in backend development, with a focus on building scalable, distributed systems.
  • Programming languages: MERN, Python, Golang. Java is optional but definitely a plus.
  • Databases: Strong experience with PostgreSQL + familiarity with NoSQL/MongoDB.
  • MLOps & Infrastructure: Knowledge of MLflow, Kubeflow, DVC, CI/CD pipelines, Docker, Kubernetes.
  • Cloud & Infra: AWS SageMaker/Bedrock, GCP Vertex AI, Azure AI.
  • Versioning & Collaboration: Git, GitHub/GitLab, code reviews, unit testing.
What We Look For:

We are looking for someone who is:

  • Startup-ready: adaptable, curious, hands-on.
  • Strong ownership + problem-solving.
  • Eager to push Generative AI into real-world adoption.

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