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Senior AI / ML Engineer

Senior AI / ML Engineer

Charter GlobalIndia
8 days ago
Job description

Job Summary :

We are looking for a results-driven Senior AI / ML Engineer to lead the development and deployment of scalable machine learning models and intelligent systems. You will be at the forefront of building AI solutions that solve high-value business problems, with full ownership from data preparation to model monitoring. This is a key role in a hands-on, production-grade AI / ML team, working with state-of-the-art tooling and infrastructure.

Key Responsibilities :

  • Design and implement robust, end-to-end ML models and AI pipelines to solve real-world business challenges.
  • Build and maintain scalable data pipelines for structured and unstructured datasets — including data extraction, cleansing, feature engineering, and labeling.
  • Train and tune ML models using modern frameworks such as TensorFlow, PyTorch, and scikit-learn.
  • Deploy models to production using MLOps tools like MLflow, Kubeflow, or Amazon SageMaker.
  • Collaborate with Product, Engineering, and Data Science teams to embed ML into customer-facing solutions.
  • Monitor and optimise models for performance, reliability, and drift detection in live environments.
  • Conduct R&D on cutting-edge techniques in LLMs, NLP, and computer vision, and apply them to production use cases.
  • Build internal dashboards, logs, and traceability features to ensure robust model governance.
  • Write clean, reusable code and maintain thorough documentation of solutions and processes.

Required Skills & Qualifications :

  • 8+ years of experience in machine learning, AI engineering, or applied data science roles.
  • Deep fluency in Python and core ML libraries : NumPy, Pandas, scikit-learn, TensorFlow, PyTorch.
  • Strong knowledge of ML algorithms, statistical modeling, and deep learning architectures (CNNs, RNNs, Transformers).
  • Experience with cloud platforms such as AWS, Azure, or GCP for training and deploying models.
  • Proficiency with Docker, Kubernetes, and DevOps tools for ML deployment.
  • Hands-on experience with MLOps frameworks like MLflow, Kubeflow, or SageMaker.
  • Familiarity with CI / CD pipelines, model registries, and version control best practices.
  • Ability to work with large-scale, multimodal datasets (text, time series, images, etc.).
  • Strong analytical, problem-solving, and collaboration skills.
  • Preferred Qualifications :

  • Master’s degree in computer science, AI, Data Science, or a related field.
  • Experience building applications using LLMs (e.g., GPT, BERT) or working on NLP and Computer Vision problems.
  • Familiarity with Big Data tools such as Spark, Kafka, Databricks.
  • Contributions to open-source ML / AI projects or peer-reviewed publications.
  • Awareness of AI ethics, data privacy regulations, and responsible AI deployment practices.
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