Chief Machine Learning Engineer

5 days ago

Dindigul, Tamil Nadu, India beBeeArtificialIntelligence Full time US$ 1,20,000 - US$ 1,80,000
Expert in Artificial Intelligence Solutions

As a skilled professional, you will design and develop sophisticated machine learning models to address complex business issues. Your work will involve creating scalable AI/ML pipelines for data ingestion, preprocessing, training, testing, deployment, and monitoring.

Key Responsibilities:

  • Develop and implement custom machine learning and deep learning models for business-specific challenges.
  • Build and maintain efficient AI/ML pipelines using best practices.
  • Collaborate with cross-functional teams to integrate AI solutions into real-world products.
  • Ensure high-performance, scalable, and production-ready deployment of AI/ML models.
  • Optimize models using advanced techniques such as hyperparameter tuning, distributed training, and GPU optimization.
  • Contribute to research initiatives and adopt the latest innovations in Large Language Models, generative AI, and automation frameworks.
  • Document technical processes and architectures for reproducibility and knowledge sharing.

Requirements:

  • Bachelor's/Master's degree in Computer Science, Artificial Intelligence, Data Science, or related field.
  • 5+ years of hands-on experience in developing AI/ML solutions.
  • Strong programming expertise in Python and popular frameworks like PyTorch, TensorFlow, Scikit-learn, Hugging Face.
  • Proven track record in building and managing ML pipelines (Airflow, Kubeflow, MLflow, Prefect, etc.).
  • Proficiency in data preprocessing, feature engineering, and model evaluation techniques.
  • Hands-on experience with cloud AI/ML platforms (AWS Sagemaker, Azure ML, or GCP Vertex AI).
  • Familiarity with containerization and orchestration (Docker, Kubernetes).
  • Strong problem-solving ability and ability to work independently in a fast-paced environment.

Preferred Skills:

  • Experience in fine-tuning Large Language Models.
  • Exposure to real-time/streaming data processing (Kafka, Spark Streaming).
  • Knowledge of microservices and API development for model integration.
  • Experience with generative AI and reinforcement learning techniques.

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