Job Description
Job Description
Responsibilities:
- Develop and implement generative AI Applications using Java and Python and leading industry tools and frameworks.
- Collaborate with data scientists and engineers to design and optimize AI/ML solutions.
- Conduct research and stay up to date with the latest advancements in generative AI and AI/ML technologies.
- Analyze large-scale datasets to identify patterns, trends, and insights that can be leveraged for AI model development.
- Optimize and fine-tune AI models to improve performance, accuracy, and efficiency.
- Work closely with product managers and stakeholders to understand business requirements and translate them into technical solutions.
- Collaborate with software engineers to integrate AI models into existing servicing applications and ensure scalability and reliability.
- Conduct code reviews and provide technical guidance and mentorship to junior team members.
- Stay abreast of industry best practices and emerging trends in AI/ML, Java, and Python development.
- Participate in cross-functional team meetings, brainstorming sessions, and knowledge sharing activities to foster innovation and continuous improvement.
- Cloud Technology Utilization: Leverage cloud platforms for ML and data engineering solutions.
- CI/CD Implementation: Implement and manage Continuous Integration and Continuous Deployment (CI/CD) processes.
- Banking Data Expertise: Utilize knowledge of banking data for relevant data engineering tasks.
- Working in Agile Environments: Experience with Agile methodologies and practices.
- Problem-Solving and Troubleshooting: Strong analytical skills to solve problems and troubleshoot issues.
Qualifications & Skills:
- Degree in Computer Science with 10+ years in experience
- Proficient in Programming Languages: Python, Java, Scala, and others.
- Proficient in writing clean and efficient code to implement machine learning algorithms.
- Deep understanding of various machine learning algorithms such as regression, classification, clustering, and deep learning
- Familiarity with popular ML frameworks such as TensorFlow, PyTorch, or scikit-learn
- Big Data Platform Proficiency: Skilled in working with Big Data platforms and Big Data lakes.
- Cloud Knowledge: Proficient in cloud computing technologies.
- Banking Data Knowledge: Familiarity with banking data structures and requirements.
- Architecture design and modeling: should possess strong skills in designing and modeling complex systems and architectures.
- Ability to create scalable, reliable, and efficient solutions that meet business requirements.
- Docker and Kubernetes Proficiency: Proficient with containerization and orchestration using Docker and Kubernetes.
- Continuous Learning: Commitment to staying updated with industry trends.
- Leadership and communication: lead teams and collaborate with stakeholders, so strong leadership and communication skills are essential.
- Ability to effectively communicate technical concepts to both technical and non-technical audiences.
- Should have excellent problem-solving and analytical skills