Senior Software Engineer (MLOps)

Key Responsibilities

• Design, develop, and maintain scalable MLOps pipelines for model deployment and monitoring.
• Collaborate with data scientists to understand model requirements and ensure seamless integration of models into production systems.
• Implement best practices for continuous integration and continuous deployment (CI/CD) in machine learning projects.
• Monitor performance and reliability of machine learning models in production environments, and optimize where necessary.
• Work with cross-functional teams, including data engineers, software developers, and product managers, to align MLOps strategies with business objectives.
• Develop and maintain documentation for MLOps processes and systems.
• Stay up-to-date with advancements in machine learning and MLOps tools and technologies.
• Mentor junior engineers and contribute to building a culture of learning and innovation within the team.

Essential Qualifications

• Bachelor’s degree in Computer Science, Engineering, or a related field; advanced degrees preferred.
• Strong proficiency in programming languages such as Python, Java, or Scala.
• Solid understanding of machine learning algorithms and frameworks (e.g., TensorFlow, PyTorch, Scikit-learn).
• Experience with cloud platforms such as AWS, Google Cloud, or Azure, particularly in the context of machine learning services.
• Familiarity with containerization and orchestration technologies (e.g., Docker, Kubernetes).
• Knowledge of database systems and data processing frameworks (e.g., SQL, NoSQL, Apache Spark).
• Understanding of software development principles, design patterns, and best practices.

Desired Experience

• 5+ years of experience in software development, with at least 2 years in MLOps or related fields.
• Experience designing and implementing end-to-end machine learning workflows in production.
• Proven track record of working with large datasets and optimizing performance of machine learning models.
• Experience in collaborating with cross-functional teams and stakeholder management.

Salary & Benefits

• Competitive annual salary based on experience.
• Comprehensive health insurance coverage.
• Paid time off and holidays.
• Professional development opportunities and support for continuous learning.
• Flexible working arrangements, including remote work options.
• Join a dynamic and collaborative work environment that values innovation and creativity.