Senior AI ML Engineer

Senior AI/ML Engineer

Roles & Responsibilities:

• Design and develop

  scalable AI/ML models and solutions

  for integration into existing systems.
• Lead

  end-to-end AI/ML lifecycle

  — from problem definition, data collection, model building, evaluation, and deployment.
• Collaborate with

  product managers, data scientists, and software engineers

  to integrate models into production systems.
• Research and implement

  state-of-the-art algorithms

  to continuously improve performance.
• Optimize AI/ML models for

  performance and scalability

  in cloud-based environments.
• Provide

  technical guidance and mentorship

  to junior team members.

Skills & Knowledge:

• Strong understanding of machine learning techniques and algorithms (regression, classification, clustering, reinforcement learning).
• Proficiency in programming languages: Python, Java, R, PySpark/Scala.
• Experience with ML frameworks and libraries: TensorFlow, PyTorch, scikit-learn, Keras.
• Hands-on expertise with cloud platforms (AWS, Azure, GCP) and deploying AI/ML models in cloud environments.
• Knowledge of big data technologies (Hadoop, Spark) for handling large-scale datasets.
• Familiarity with DevOps practices and CI/CD pipelines.

Requirements:

• 3–5 years of experience in designing and implementing machine learning solutions in a production environment.
• Proven track record of delivering AI/ML projects from concept to production.
• Ability to work collaboratively in cross-functional teams.

Education & Certification:

• Education:

  Bachelor’s degree in Computer Science, Engineering, Mathematics, or related technical field.

Preferred Certifications:

• Machine Learning or AI certifications (e.g., AWS Certified Machine Learning – Specialty, Google Cloud Professional ML Engineer, Microsoft Certified Azure AI Engineer Associate).
• Big Data or Cloud certifications are an added advantage.