Advanced Data Scientist

12 hours ago

Hyderabad, Telangana, India beBeeMachineLearning Full time ₹ 1,50,00,000 - ₹ 2,50,00,000

**Machine Learning Engineer Position**

Job Description:

As a skilled Machine Learning Engineer, you will play a crucial role in developing and deploying cutting-edge machine learning solutions that directly impact our core business functions and enhance user experiences.

In this position, you will be responsible for designing, developing, and implementing end-to-end machine learning models, from initial data exploration and feature engineering to model deployment and monitoring in production environments.

You will work closely with cross-functional teams to translate business requirements into effective, scalable, and maintainable ML solutions.

Additionally, you will be expected to build and optimize data pipelines for both structured and unstructured datasets, leveraging advanced data blending, transformation, and cleansing techniques to ensure data quality and readiness for modeling.

Key Responsibilities:

  • Design and develop machine learning models, including initial data exploration and feature engineering, model training, and deployment in production environments.
  • Build and optimize data pipelines for structured and unstructured datasets, using advanced data blending and transformation techniques.
  • Collaborate with data scientists, software engineers, and product managers to translate business requirements into effective ML solutions.
  • Implement and maintain robust MLOps practices, including version control, model monitoring, logging, and performance evaluation.
  • Research and experiment with new machine learning techniques, tools, and technologies to enhance predictive capabilities and operational efficiency.
Required Skills & Qualifications:

Essential Requirements:

  • 5+ years of hands-on experience in building, training, and deploying machine learning models in a professional setting.
  • Demonstrable experience with database creation and advanced querying (e.g., SQL, NoSQL), with a strong understanding of data warehousing concepts.
  • Proven expertise in data blending, transformation, and feature engineering, adept at integrating and harmonizing structured and unstructured data.
  • Strong practical experience with cloud platforms for machine learning development and deployment; significant experience with Google Cloud Platform services is highly desirable.
  • Proficiency in programming languages commonly used in data science (e.g., Python).

Desirable Requirements:

  • Experience with machine learning libraries and frameworks (e.g., scikit-learn, TensorFlow, PyTorch).
  • Familiarity with MLOps tools and practices, including model versioning, monitoring, A/B testing, and continuous integration/continuous deployment pipelines.
  • Experience with containerization technologies like Docker and orchestration tools like Kubernetes for deploying ML models as REST APIs.
  • Proficiency with version control systems (e.g., Git, GitHub/GitLab) for collaborative development.

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