Lead Systems Engineer - Data DevOps/MLOps

As a Lead Systems Engineer with Data DevOps/MLOps expertise, your role is crucial in driving innovation and efficiency across data and machine learning operations. You will be responsible for designing, deploying, and managing CI/CD pipelines to ensure seamless data integration and ML model deployment. Your key responsibilities include: - Establishing robust infrastructure for processing, training, and serving machine learning models using cloud-based solutions - Automating critical workflows such as data validation, transformation, and orchestration for streamlined operations - Collaborating with cross-functional teams to integrate ML solutions into production environments - Improving model serving, performance monitoring, and reliability in production ecosystems - Ensuring data versioning, lineage tracking, and reproducibility across ML experiments and workflows - Identifying and implementing opportunities to enhance scalability, efficiency, and resilience of the infrastructure - Enforcing rigorous security measures to safeguard data and ensure compliance with relevant regulations - Debugging and resolving technical issues in data pipelines and ML deployment workflows Qualifications required for this role include: - Bachelors or Masters degree in Computer Science, Data Engineering, or a related field - 8+ years of experience in Data DevOps, MLOps, or related disciplines - Expertise in cloud platforms such as Azure, AWS, or GCP - Skills in Infrastructure as Code tools like Terraform, CloudFormation, or Ansible - Proficiency in containerization and orchestration technologies such as Docker and Kubernetes - Hands-on experience with data processing frameworks including Apache Spark and Databricks - Proficiency in Python with familiarity with libraries including Pandas, TensorFlow, and PyTorch - Knowledge of CI/CD tools such as Jenkins, GitLab CI/CD, and GitHub Actions - Experience with version control systems and MLOps platforms including Git, MLflow, and Kubeflow - Understanding of monitoring and alerting tools like Prometheus and Grafana - Strong problem-solving and independent decision-making capabilities - Effective communication and technical documentation skills Nice to have qualifications may include: - Background in DataOps methodologies and tools such as Airflow or dbt - Knowledge of data governance platforms like Collibra - Familiarity with Big Data technologies such as Hadoop or Hive - Showcase of certifications in cloud platforms or data engineering tools Overall, your role as a Lead Systems Engineer will be pivotal in driving the success and efficiency of data and machine learning operations within the company.,