What does a successful Senior Machine Learning Engineer do at Fiserv?
Harnesses advanced analytics and machine learning to derive AI Ops initiatives, optimizing AI operations and system performance. This role involves collaborating with cross-functional teams to identify business needs and develop data-driven solutions that enhance operational efficiency and decision-making. By deploying and maintaining AI solutions, the Senior ML Engineer ensures they operate effectively across the organization.
What you will do:
- Develop and implement machine learning models and algorithms to optimize AI operations and enhance system performance.
- Collaborate with cross-functional teams to identify business needs and translate them into data-driven solutions.
- Analyze large datasets to extract actionable insights and support strategic decision-making.
- Design and conduct experiments to validate model performance and improve operational processes.
- Monitor and maintain AI models in production to ensure effective and efficient operation.
- Communicate findings and recommendations to stakeholders through clear visualizations and presentations.
What you will need to have:
- 10+ years of experience in data science, focusing on AI and machine learning applications.
- 8+ years of experience in programming with Python, R, or Scala and using data manipulation libraries like Pandas, Numpy.
- 7+ years of experience working with machine learning frameworks such as TensorFlow, PyTorch, or Scikit-learn.
- 6+ years of experience with cloud platforms like AWS or Azure and big data technologies such as Hadoop, Spark.
- Master’s or Ph.D. in Data Science, Computer Science, Statistics, or a related field, and/or equivalent military experience.
What would be great to have:
- 5+ years of experience designing and deploying end-to-end machine learning pipelines in production environments.
- 4+ years of expertise in natural language processing (NLP) and computer vision techniques.
- 3+ years of knowledge in reinforcement learning and its practical applications.
- 4+ years of experience with ML Ops tools and practices for continuous integration and deployment of machine learning models.
- 3+ years of familiarity with regulatory and compliance considerations for AI and machine learning solutions.
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