Senior ML Engineer with strong Machine Learning infrastructure :: Remote

Job title: Senior ML Engineer with strong Machine Learning infrastructure
Location: San Diego, CA(Remote)
Mandatory Skills: Machine Learning infrastructure, A/B testing, CI/CD workflows

Job Description:

This role requires a hands-on engineer who excels in building, deploying, and maintaining scalable ML solutions within a product environment. The successful candidate will work on productionizing ML models, managing data pipelines, implementing CI/CD workflows, and conducting A/B testing to ensure the highest quality and performance of AI-driven products. You will work closely with cross-functional teams, including AI leads, ML scientists, MLOps engineers, and product owners, to develop cutting-edge solutions that impact millions of lives worldwide.

Responsibilities:

• Work closely with ML/CV/NLP scientists, and MLOps engineers to engineer, deploy, and optimize machine learning models to scale across production environments, ensuring robustness and reliability.
• Design and implement efficient data management and data processing pipelines to handle large volumes of structured and unstructured data.
• Write clean, modular, and maintainable code following best practices in software engineering, with an emphasis on scalability and performance.
• Build and maintain continuous integration and continuous delivery (CI/CD) pipelines to automate model training, testing, and deployment.
• Implement and manage A/B testing frameworks to evaluate model performance and ensure alignment with business objectives.
• Work closely with data scientists, MLOps engineers, product managers, and software engineers to align on requirements and successfully integrate ML solutions into products.
• Develop monitoring solutions to ensure models are performing optimally in production, addressing issues proactively to maintain service quality.
• Create and maintain comprehensive documentation for code, workflows, and system architecture to facilitate knowledge sharing and maintainability.

Qualifications:

• BSc. or MSc. degree in Computer Science, Engineering, Data Science, or a related field.
• Minimum of 5 years of hands-on experience in machine learning engineering, with a strong focus on productionizing models and building ML infrastructure.
• Proficiency in Python, with experience in Java, Scala, or similar programming languages.
• Experience with ML and DL frameworks (e.g., TensorFlow, PyTorch, Scikit-Learn).
• Strong understanding of CI/CD best practices and experience with tools like Jenkins, GitLab CI, or similar.
• Knowledge of A/B testing frameworks and model validation techniques.
• Proficiency in building and maintaining data processing pipelines using tools like Apache Spark, Airflow, or Kafka.
• Familiarity with cloud services (e.g., AWS, Google Cloud Platform, or Azure) and containerization tools (e.g., Docker, Kubernetes).
• Experience building APIs with frameworks such as Streamlit, Flask, or FastAPI for model deployment and interaction.
• Strong understanding of software engineering principles, including object-oriented programming, version control, and testing frameworks.
• Experience in developing scalable and maintainable code for real-world applications.
• Excellent problem-solving abilities and analytical mindset.
• Strong communication skills, both written and verbal.
• Ability to work collaboratively in an Agile environment with cross-functional teams.