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AI / ML Engineer

AI / ML Engineer

LIVE CONNECTIONSHyderabad
30+ days ago
Job description

Job Description :

Key Responsibilities :

  • Collaborate with data scientists and stakeholders to understand project requirements and define the scope of AI / ML solutions.
  • Design and develop machine learning models and algorithms based on business needs and available data.
  • Clean, preprocess, and analyze large datasets to prepare them for model training.
  • Train, evaluate, and fine-tune machine learning models to optimize performance and accuracy.
  • Implement and deploy AI / ML models into production environments.
  • Monitor and maintain deployed models, ensuring their performance and reliability.
  • Build and optimize data pipelines and MLOps workflows.
  • Stay updated on the latest research, techniques, and technologies in the fields of Artificial Intelligence and Machine Learning.
  • Participate in code reviews and contribute to the improvement of development and deployment processes.
  • Collaborate effectively with software engineers, data engineers, and other cross-functional teams.

Required Skills & Qualifications :

  • Experience as an AI / ML Engineer or in a similar role.
  • Strong understanding of fundamental Machine Learning algorithms (e.g., linear regression, logistic regression, tree-based models, clustering).
  • Proficiency in programming languages commonly used in AI / ML, primarily Python.
  • Experience with key ML libraries and frameworks such as TensorFlow, PyTorch, scikit-learn, Keras, etc.
  • Experience with data manipulation and analysis libraries like Pandas and NumPy.
  • Ability to perform data preprocessing, feature engineering, and exploratory data analysis.
  • Knowledge of model evaluation techniques and metrics.
  • Familiarity with model deployment strategies and MLOps concepts.
  • Experience with version control systems, preferably Git.
  • Strong analytical and problem-solving skills.
  • Excellent communication and collaboration skills.

    • Desired Skills (Plus Points) :

  • Experience with Deep Learning techniques and frameworks.
  • Experience with specific domains such as Natural Language Processing (NLP) or Computer Vision.
  • Experience with cloud platforms and their AI / ML services (e.g., AWS SageMaker, Azure ML, Google AI Platform).
  • Experience with big data technologies (e.g., Spark, Hadoop).
  • Knowledge of containerization (e.g., Docker).
  • Experience with A / B testing and experimentation.
  • Advanced degree (Master's or Ph.D.) in a quantitative field such as Computer Science, Statistics, Mathematics, or a related discipline.

    • ref : hirist.tech)

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