About the job
At SunnyData, we are dedicated to empowering our clients by constructing highly scalable architectures, developing robust data engineering pipelines, and creating user-friendly data consumption layers. Most importantly, we focus on building advanced Machine Learning (ML) and Artificial Intelligence (AI) applications that drive exceptional business outcomes. As a Senior Machine Learning Engineer, you will spearhead intricate data projects, design predictive models, and implement scalable machine learning solutions. You will collaborate across various teams including engineering, product, and analytics to generate actionable insights and impact critical business decisions.
Your Contribution
Lead the architecture, development, and deployment of machine learning models.
Work with extensive and intricate datasets to extract valuable insights and establish predictive analytics pipelines.
Partner with data engineers to design and enhance cloud-based data solutions.
Convert business challenges into data-driven strategies utilizing statistical modeling and machine learning methodologies.
Streamline data workflows and model deployment processes using cloud services and CI/CD methodologies.
Guide junior data scientists and contribute to the establishment of best practices in model development and implementation.
Effectively communicate insights and strategic recommendations to stakeholders and executive leadership.
Desired Qualifications
A minimum of 5 years of experience in data science or machine learning positions.
Strong proficiency in Python (including libraries such as pandas, scikit-learn, PyTorch, or TensorFlow) and SQL.
A solid foundation in statistics, A/B testing, and machine learning algorithms.
Proven experience in building and deploying models in production settings.
Familiar with MLOps tools and practices (e.g., MLflow, SageMaker Pipelines, Airflow).
Exceptional communication and leadership capabilities.
Preferred Qualifications
Experience with big data technologies (e.g., Spark, EMR).
Familiarity with containerization technologies (e.g., Docker, ECS, EKS) and serverless architectures.
Education
Bachelor’s or Master’s degree in Computer Science, Statistics, Mathematics, or a related field is preferred.
