AI/ML Engineering Leader
1 week ago
Job Title: AI/ML Engineering Leader
Location: PAN India
Estimated Salary: ₹2,500,000 - ₹3,500,000 per annum
At Tata Consultancy Services, we are seeking an experienced Ai/ml engineering leader to join our team. As a key member of our organization, you will be responsible for leading the design, development, and deployment of machine learning models and AI systems to address healthcare challenges.
The ideal candidate will have a strong background in data science, machine learning, or AI engineering, with experience in leading and mentoring technical teams. You will work closely with cross-functional teams, including clinicians, researchers, and IT, to identify business needs and translate them into technical solutions.
Responsibilities:
- Lead the design, development, and deployment of machine learning models and AI systems to address healthcare challenges.
- Collaborate with cross-functional teams to identify business needs and translate them into technical solutions.
- Develop and implement advanced algorithms and statistical models to solve healthcare-specific problems.
- Optimize and enhance existing machine learning models for better performance and scalability in healthcare settings.
- Apply software engineering rigor and best practices to machine learning, including CI/CD, automation, etc.
- Mentor and guide junior data scientists and engineers, fostering a culture of continuous learning and improvement.
Requirements:
- 4+ years of experience in data science, machine learning, or AI engineering roles like GenAI, Statistical Analysis, Data Mining, and Data Visualization.
- 3+ years of experience with software engineering using Java, .net, python or any backend and frontend languages.
- 3+ years of experience in Deploying and operationalizing ML Ops.
- Experience in leading and mentoring technical teams.
- Proven track record of successfully delivering AI/ML projects from conception to deployment.
Preferred Qualifications:
- Experience with Azure Databricks, Azure Data Factory, SQL Server/NOSQL Databases, Azure ML Studio.
- Model evaluation and explainability.
- Model training and automated retraining.
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