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Wadhwani Foundation
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AI Engineer - WGDT

AI Engineer - WGDT

Wadhwani Foundation

5 - 10 years

7 - 12 Lacs

kolkata mumbai new delhi hyderabad pune chennai bengaluru

Posted:3 weeks ago| Platform:

Apply

Skills Required

training c++ analytical machine learning manager technology deployment data quality digital transformation monitoring python

Work Mode

Work from Office

Job Type

Full Time

Job Description

The Role Context:

This is an exciting opportunity to join a dynamic and growing organization,working at the forefront of technology trends and developments in social impactsector. Wadhwani Center for Government Digital Transformation (WGDT) works withthe government ministries and state departments in India with a mission of Enablingdigital transformation to enhance the impact of government policy, initiativesand programs .

We are seeking a highly motivated anddetail-oriented individual to join our team as a AI Engineer withexperience in developing cutting-edge AI/GenAI solutions that drive innovationand contribute to the successful implementation of digital government policiesand programs. You will collaborate with cross-functional teams to design,implement, and deploy AI models and algorithms to solve complex problems and optimizingbusiness processes across various government ministries and state departmentsin India.

Key Responsibilities:

Develop and implement AI/GenAI models and algorithms to address business challenges and improve operational efficiency.
Collaborate with data scientists and software engineers to design and deploy scalable AI solutions.
Research and evaluate new AI technologies, frameworks, and tools to enhance our capabilities and stay ahead of industry trends.
Design and optimize machine learning pipelines for data preprocessing, feature engineering, model training, and evaluation.
Work closely with product managers and stakeholders to understand requirements and translate them into actionable AI solutions.
Conduct experiments and analyze data to measure the performance of AI models and identify areas for improvement.
Ensure the reliability, scalability, and maintainability of AI systems in production environments.
Stay up-to-date with the latest advancements in AI, machine learning, GenAI and related fields, and share knowledge with the team through presentations, workshops, and technical discussions.

Desired Skills/ Competencies

a) Bachelors or Masters degree in Computer Science, SoftwareEngineering, Data Science mathematics, or a related field with at least 5 yearsof experience.

b) Solid understanding of machine learning algorithms,deep learning frameworks (e.g., TensorFlow, PyTorch), and AI techniques.

c) Proficiency in programming languages such asPython, Java, or C++.

d) Experience with data processing and manipulationlibraries (e.g., NumPy, Pandas) and big data technologies (e.g., Spark, Hadoop.Object stores, Databricks, etc.).

e) Strong analytical and problem-solving skills, withthe ability to interpret complex data and draw meaningful insights.

f) Excellent communication and collaboration skills,with the ability to work effectively in a team environment.

g) Prior experience in deploying AI models inproduction environments is a plus.

h) Familiarity with cloud platforms (e.g., AWS, Azure,Google Cloud) and containerization technologies (e.g., Docker, Kubernetes) isdesirable.

KPIs:

1. Model Performance Metrics : Accuracy, precision, recall, F1 score, and other relevant metricsspecific to the AI models being developed for government ministries andprogram.

2. Model Efficiency : Time taken for model training, inference time, and resourceutilization (e.g., CPU/GPU usage, memory consumption).

3. Data Quality and Quantity : Measurement of data completeness, correctness, and diversity to ensurerobust model performance.

4. Feature Engineering : Efficiency in feature selection, transformation, and extraction toenhance model accuracy and efficiency.

5. Model Deployment Time : Time taken from model development to deployment in productionenvironments.

6. System Reliability : Monitoring system uptime, error rates, and response times to ensureconsistent AI services.

7. Feedback Loop Effectiveness : Ability to incorporate feedback from users or other systems toiteratively improve models.

8. Model Interpretability : Development and implementation of techniques to explain AI modelpredictions and decisions.

9. Continuous Learning : Engagement in ongoing learning activities to stay updated with thelatest AI techniques, technologies, and best practices.

10. Collaboration and Communication : Effectiveness in collaborating with cross-functional teams andcommunicating technical concepts to non-technical stakeholders of variousstakeholders involved in the government program.

Years of experience of the current role holder

New Position

Ideal years of experience

3-5 years

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