Senior Machine Learning Engineer

Location: Remote

Experience: 6+ Years

: We are seeking an experienced Machine Learning Engineer with 6+ years of expertise to join our dynamic team. The ideal candidate will possess in-depth knowledge of machine learning frameworks and tools, coupled with experience in deploying and managing ML models at scale. This is a remote position offering the opportunity to work on challenging projects in a collaborative environment.

Key Responsibilities:

• Design, develop, and deploy machine learning models and pipelines using TensorFlow, PyTorch, and Scikit-learn.
• Build and optimize ETL workflows for large-scale data processing.
• Integrate and manage CI/CD pipelines for seamless model deployment.
• Collaborate with cross-functional teams to define requirements and deliver high-quality ML solutions.
• Containerize ML applications using Docker and manage orchestration with Kubernetes.
  
• Leverage cloud platforms (AWS, Azure) for scalable ML model training and deployment.
• Implement and manage distributed computing frameworks like Apache Spark.
• Monitor and improve model performance, addressing issues like drift and retraining.
• Document best practices, frameworks, and workflows to support knowledge sharing within the team.

Required Skills and Qualifications:

• Bachelors or Masters degree in Computer Science, Data Science, or a related field.
• 6+ years of experience in machine learning engineering and deployment.
• Strong programming skills in Python and familiarity with frameworks like TensorFlow, PyTorch, and Scikit-learn.
• Proficiency in cloud platforms such as AWS and Azure.
• Hands-on experience with Docker and Kubernetes for containerization and orchestration.
• Expertise in CI/CD tools like Jenkins and version control systems like Git.

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• Solid understanding of ETL processes and distributed computing frameworks such as Apache Spark.
• Strong problem-solving skills and the ability to work effectively in a remote setting.
• Excellent communication skills to collaborate with cross-functional teams and stakeholders.

Preferred Skills:

• Experience with MLflow for model tracking and monitoring.
• Familiarity with data versioning tools and feature stores.
• Knowledge of infrastructure-as-code tools like Terraform or Ansible.
• Certification in relevant cloud platforms or ML-related domains.
• Awareness of ethical considerations and data privacy regulations in ML.

python, scala, sql ,sensor flow, pystroch,skytit,jenkins.HGIT,CLOUD ,AAWS, ETL- SQL