Senior ML Engineer

Key Responsibilities

• Design, develop, and deploy

  end-to-end machine learning models

  into production environments.
• Build and maintain

  scalable data pipelines

  , model training workflows, and automated processes.
• Collaborate with data scientists, data engineers, and product teams to translate business needs into ML-driven solutions.
• Conduct model experimentation, evaluation, and optimization to improve performance and reliability.
• Implement

  MLOps best practices

  , including CI/CD, model monitoring, and retraining workflows.

Required Qualifications

• 8+ years of professional experience

  in machine learning engineering or a related field.
• Strong proficiency in

  Python

  and ML frameworks such as

  TensorFlow, PyTorch, Scikit-learn

  .
• Hands-on experience with

  cloud platforms

  (AWS, GCP, or Azure) and ML services (SageMaker, Vertex AI, etc.).
• Solid understanding of

  data structures, algorithms, and software engineering principles

  .
• Experience with

  MLOps tools

  (Docker, Kubernetes, MLflow, Airflow, Kubeflow, etc.).
• Proven ability to build

  production-grade ML systems

  and scalable APIs.
• Strong knowledge of model evaluation techniques and performance optimization.
• Experience working in

  remote, distributed teams

  is a plus.

Preferred Qualifications

• Experience with

  big data tools

  (Spark, Hadoop, Databricks).
• Knowledge of

  feature store

  systems and model monitoring platforms.
• Familiarity with

  CI/CD pipelines

  (GitHub Actions, Jenkins, GitLab CI).