AI/ML Engineer

Key Responsibilities

• AI/ML Model Development:

• Design, develop, and deploy machine learning models and AI solutions for real-world applications.

• Data Engineering & Integration:

• Build and optimize data pipelines to support AI/ML workflows and ensure seamless integration with existing systems.

• Generative & Agentic AI Exposure (Preferred):

• Work on emerging AI technologies such as Generative AI and Agentic AI for advanced use cases.

• Data Analysis & Visualization:

• Collect, clean, and preprocess large datasets; perform statistical analysis and create dashboards to derive actionable insights.

• Collaboration:

• Partner with engineers, data scientists, and product teams to deliver scalable AI-driven solutions.

• Performance Optimization:

• Fine-tune models for accuracy, efficiency, and scalability in production environments.

Required Qualifications

• Experience:

• Minimum 3 years in AI/ML development with exposure to data engineering concepts.

• Technical Skills:

• Programming:

  Proficiency in Python or R; Deep knowledge of SQL and data manipulation.

• AI/ML Frameworks:

  Hands-on experience with TensorFlow, PyTorch, or similar.

• Data Handling:

  Strong skills in managing large datasets and building ETL pipelines.

• Cloud Platforms:

  Familiarity with AWS, GCP, or Azure for AI/ML deployments.

• APIs:

  Experience in developing REST APIs for model integration.

• Core Competencies:

• Analytical mindset, problem-solving skills, and ability to work in agile environments.

Preferred Skills

• Exposure to

  Generative AI

  ,

  Agentic AI

  ,

  NLP

  , or

  Deep Learning

  .
• Experience with

  Big Data technologies

  (Hadoop, Spark).
• Understanding of

  MLOps

  and deployment of models in production.