Here is the Job description: (or Kindly share your updated cv at [email protected])
AI & ML Model Development & Architecture:
- Design, develop, and implement AI/ML solutions using CNN, RNN, and other advanced neural network architectures to solve complex real-world problems in areas such as computer vision, natural language processing, and time-series forecasting.
- Lead the development of end-to-end machine learning pipelines using frameworks like TensorFlow, PyTorch, Keras, and Hugging Face.
- Develop and fine-tune machine learning models for specific business needs and ensure robust model performance.
- Apply probability theory, statistics, and optimization techniques to develop reliable and scalable models.
Leadership & Mentorship:
- Lead and mentor a team of AI/ML engineers, providing technical direction, code reviews, and hands-on training to ensure the team is following best practices in model development and deployment.
- Foster a collaborative work environment and encourage knowledge sharing across teams.
- Coordinate cross-functional teams to ensure AI solutions are aligned with business goals and technical feasibility.
Cloud Platform Expertise & Deployment:
- Utilize AWS SageMaker, Azure AI Foundry, and other cloud platforms to deploy scalable machine learning models and manage ML workflows.
- Oversee the deployment of models into production, ensuring high availability, reliability, and performance.
- Manage cloud-based resources efficiently, ensuring cost-effective use of infrastructure.
Research & Innovation:
- Keep up with the latest AI/ML research and advancements, and experiment with emerging algorithms and techniques to maintain a competitive edge.
- Drive research on new techniques in time-series forecasting, deep learning, and other AI methodologies to continuously improve product offerings.
- Contribute to the academic community and industry advancements by publishing research, whitepapers, or speaking at conferences.
Model Optimization & Performance:
- Continuously monitor model performance in production, conducting regular model tuning and improvements.
- Ensure that the models are interpretable and explainable, providing insights to business stakeholders.
- Focus on improving model accuracy, efficiency, and robustness across all platforms.
Stakeholder Collaboration:
- Work with product managers, business analysts, and other key stakeholders to define AI/ML use cases, prioritize projects, and deliver solutions that meet business needs.
- Present complex AI/ML concepts and results to non-technical stakeholders, translating technical solutions into actionable insights.
Time-Series & Advanced Analytics:
- Lead the development of time-series forecasting models for business applications, such as demand forecasting, anomaly detection, and trend analysis.
- Develop statistical models based on time-series data, applying techniques like ARIMA, LSTM, or Prophet.
Model Governance & Compliance:
- Ensure that AI models and machine learning systems adhere to industry regulations and compliance standards, such as GDPR and data privacy laws.
- Establish best practices for model governance, including versioning, performance tracking, and documentation.
Pay: Up to ₹1,400,000.00 per year
Benefits:
- Health insurance
- Paid time off
- Provident Fund
Application Question(s):
- What is your relevant exp. as Sr. AI Engineer?
- Do you have any exp. in team leading?
- Current ctc in hand?
- Expected ctc in hand?
- Notice period in days?
Experience:
Location:
- Noida, Uttar Pradesh (Noida) (Required)
Work Location: In person
