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ML II Engineer

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Hybrid

ML II Engineer

Syneos Health

ML II Engineer

Skills

SQL QueriesPythonData VisualizationJavaNumPypandasKerasTensorFlowRGitMachine LearningAWSAzure

1 month ago

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Important information


Contract type:

Permanent

Location:

Hyderabad, Telangana, India

Work mode:

Hybrid

Published on:

10 September 2026

What they need


The Machine Learning Engineer II will be responsible for supporting the deployment and maintenance of machine learning models under the guidance of senior engineers. This role assists in data preprocessing, feature engineering, model training, and evaluation tasks. This role involves learning and applying machine learning algorithms and tools to real-world problems. The ML Engineer II will collaborate with team members to ensure project milestones are met.

Job Responsibilities

  • Assist in developing and deploying basic machine learning models under supervision.
  • Perform data preprocessing, cleaning, and transformation tasks.
  • Support model training, testing, and validation processes.
  • Contribute to documentation and reporting of model performance and results.
  • Collaborate with senior engineers and data scientists to understand project requirements.
  • Participate in code reviews and contribute to maintaining code quality.
  • Continuously learn and apply new machine learning techniques and tools.

Qualification Requirements

Basic Qualifications

  • Bachelor's degree in Computer Science, Engineering, Mathematics, or a related field.
  • Three (3) to four (4) years of ML Engineering experience.
  • Understanding of machine learning algorithms and data structures.
  • Experience with SQL for querying.
  • Experience with data manipulation libraries (e.g., NumPy, Pandas).
  • Experience with machine learning libraries (e.g., scikit-learn, TensorFlow, Keras).
  • Strong problem-solving skills and attention to detail.
  • Ability to work collaboratively in a team setting and follow technical guidance.

Preferred Qualifications

  • Experience with data visualization tools (e.g., Matplotlib, Seaborn).
  • Experience with version control systems (e.g., Git).
  • Knowledge of cloud platforms from cloud service providers such as AWS or Azure.
  • Experience with programming languages such as R, Python, or Java.
  • Participation in machine learning competitions or projects.
  • Willingness to pursue further certifications or education.

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