Experience Required

3 - 6 Years

No of Position

3

Job Description

We are looking for a highly skilled AI Engineer who is passionate about building intelligent, scalable, and high-performing AI-powered solutions. As an AI Engineer, you will be responsible for developing, deploying, and optimizing machine learning models and AI services integrated into our cloud-based offerings. You’ll work closely with Developers, Architects, Engineers, and Product Managers to bring AI-driven features from concept to production.

Key Responsibilities

  • Design, build, and maintain AI/ML pipelines for production-ready applications.
  • Develop machine learning models and integrate them into scalable systems.
  • Translate business requirements into technical implementations using AI tools and technologies.
  • Collaborate with cross-functional teams to gather requirements and deliver AI features that add value to end users.
  • Write clean, maintainable, and optimized code in Python, adhering to industry standards.
  • Work on natural language processing (NLP), computer vision, recommendation engines, or predictive analytics depending on project needs.
  • Optimize models for performance, scalability, and accuracy.
  • Build APIs to expose AI capabilities and integrate them with cloud infrastructure.
  • Evaluate and use cloud-based AI tools from AWS, Azure, or other providers.
  • Continuously monitor and improve AI models in production environments.
  • Participate in code reviews, contribute to system design discussions, and document all technical solutions.

Required Skills & Experience

  • 3–6 years of overall development experience with at least 2 years in AI/ML projects.
  • Proficiency in Python, with strong understanding of libraries like TensorFlow, PyTorch, Scikit-learn, Pandas, NumPy.
  • Hands-on experience building and deploying machine learning models.
  • Experience working with REST APIs and microservices.
  • Familiarity with cloud services (AWS preferred) for AI/ML development and deployment.
  • Understanding of DevOps/CI-CD practices and MLOps tools is a plus.
  • Strong knowledge of data structures, algorithms, and object-oriented programming (OOP).
  • Ability to independently work on model training, tuning, evaluation, and deployment.

Nice to Have

  • Experience with Django/Flask web frameworks.
  • Exposure to NLP, OCR, image processing, or large language models (LLMs).
  • Familiarity with data engineering tools like Airflow, Spark, or Kafka.
  • Containerization (Docker) and orchestration (Kubernetes) experience.
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