At SunnyData, our mission is to help customers build a highly scalable architecture, robust data engineering pipelines, easy data consumption layers and more importantly build ML and AI applications to power their business and drive outstanding business outcomes. As a Machine Learning Engineer you will lead complex data projects, develop predictive models, and deploy scalable machine learning solutions. You will work cross-functionally with engineering, product, and analytics teams to derive actionable insights and influence key business decisions.
The Impact You Will Have
Lead the design, development, and deployment of machine learning models.
Work with large, complex datasets to extract valuable insights and build predictive analytics pipelines.
Collaborate with data engineers to architect and optimize cloud-based data solutions.
Translate business challenges into data-driven solutions using statistical modeling and machine learning techniques.
Automate data workflows and model deployment processes using cloud services and CI/CD tools.
Mentor junior data scientists and contribute to best practices in model development and operationalization.
Communicate findings and strategic recommendations to stakeholders and executive leadership.
What We Look For
4+ years of experience in data science or machine learning roles.
Proficient in Python (pandas, scikit-learn, PyTorch or TensorFlow) and SQL.
Strong background in statistics, A/B testing, and machine learning algorithms.
Experience building and deploying models in production environments.
Familiarity with MLOps practices and tools (e.g., MLflow, SageMaker Pipelines, Airflow).
Excellent communication and leadership skills.
Preferred Qualifications
Experience with big data tools (Spark, EMR).
Familiarity with containerization (Docker, ECS, EKS) and serverless architecture.
Education
Bachelor’s or Master’s degree in Computer Science, Statistics, Mathematics, or a related field is preferred.
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