Python Developer
Ready to shape the future of work?
At Genpact, we don’t just adapt to change—we drive it. AI and digital innovation are redefining industries, and we’re leading the charge. Genpact’s AI Gigafactory, our industry-first accelerator, is an example of how we’re scaling advanced technology solutions to help global enterprises work smarter, grow faster, and transform at scale. From large-scale models to agentic AI, our breakthrough solutions tackle companies’ most complex challenges.
If you thrive in a fast-moving, tech-driven environment, love solving real-world problems, and want to be part of a team that’s shaping the future, this is your moment.
Genpact (NYSE: G) is an advanced technology services and solutions company that delivers lasting value for leading enterprises globally. Through our deep business knowledge, operational excellence, and cutting-edge solutions – we help companies across industries get ahead and stay ahead. Powered by curiosity, courage, and innovation, our teams implement data, technology, and AI to create tomorrow, today. Get to know us at genpact.com and on LinkedIn, X, YouTube, and Facebook.
Inviting applications for the role of Python Developer with AI
Role Summary: We are looking for a highly skilled and enthusiastic Python Developer with a strong background in Artificial Intelligence to join our dynamic team at Genpact. In this role, you will be instrumental in designing, developing, and deploying cutting-edge AI/ML solutions that drive business value. You'll work on end-to-end ML workflows, from data ingestion and feature engineering to model deployment and monitoring, contributing significantly to our advanced analytics capabilities.
Responsibilities:
- Design, develop, and implement robust and scalable AI/ML applications using Python.
- Develop data processing pipelines, leveraging PySpark for large-scale data transformation and analysis.
- Write efficient SQL queries to extract, manipulate, and analyze data from various relational databases.
- Collaborate with data scientists and business stakeholders to understand requirements and translate them into technical specifications.
- Implement and optimize machine learning algorithms, focusing on performance, scalability, and interpretability.
- Develop and manage data ingestion and feature engineering pipelines, ensuring data quality and readiness for model training.
- Contributes to the implementation of end-to-end ML workflows, including model development, validation, deployment, and monitoring.
- Utilize tools and practices for model management (e.g., MLflow), version control for ML models, and CI/CD pipelines to ensure reproducibility and efficient deployment.
- Participate in code reviews, ensuring best practices for code quality, security, and maintainability.
- Monitor model performance, detect drift, and implement strategies for continuous model retraining and improvement.
- Explore and integrate new technologies and methodologies to enhance our AI capabilities.
- Ensure compliance with model risk management (MRM) requirements and established governance frameworks.
Qualification:
- Bachelor's degree in computer science, Engineering, Data Science, or a related field.
- 3+ years of professional experience in software development with a strong focus on Python .
- Proficiency in writing and optimizing complex SQL queries for data manipulation and analysis.
- Demonstrable experience with PySpark for distributed data processing and ETL operations.
- Solid understanding of machine learning principles, algorithms, and AI concepts.
- Experience with common Python ML/AI libraries (e.g., scikit-learn, TensorFlow, PyTorch).
- Familiarity with version control systems (e.g., Git).
- Strong problem-solving skills and the ability to work independently and as part of a team.
- Excellent communication skills to articulate technical concepts to both technical and non-technical audiences.
Good to Have:
- Experience with Graph Databases (e.g., Neo4j, Amazon Neptune) and graph algorithms.
- Familiarity with cloud platforms (AWS, Azure, GCP) and their AI/ML services.
- Experience with MLOps practices, CI/CD pipelines for ML, and tools like MLflow.
- Knowledge of data governance practices, including concepts like Unity Catalog.
- Experience with model validation frameworks and monitoring tools for model performance and drift.
Why join Genpact?
- Be a transformation leader – Work at the cutting edge of AI, automation, and digital innovation
- Make an impact – Drive change for global enterprises and solve business challenges that matter
- Accelerate your career – Get hands-on experience, mentorship, and continuous learning opportunities
- Work with the best – Join 140,000+ bold thinkers and problem-solvers who push boundaries every day
- Thrive in a values-driven culture – Our courage, curiosity, and incisiveness - built on a foundation of integrity and inclusion - allow your ideas to fuel progress
Come join the tech shapers and growth makers at Genpact and take your career in the only direction that matters: Up.
Let’s build tomorrow together. The approximate annual base compensation range for this position is $90k - $100k CAD per annum. The actual offer, reflecting the total compensation package plus benefits, will be determined by a number of factors which include but are not limited to the applicant’s experience, knowledge, skills, and abilities; geographic location; and internal equity
Genpact is an Equal Opportunity Employer and considers applicants for all positions without regard to race, color, religion or belief, sex, age, national origin, citizenship status, marital status, military/veteran status, genetic information, sexual orientation, gender identity, physical or mental disability or any other characteristic protected by applicable laws. Genpact is committed to creating a dynamic work environment that values respect and integrity, customer focus, and innovation.
Furthermore, please do note that Genpact does not charge fees to process job applications and applicants are not required to pay to participate in our hiring process in any other way. Examples of such scams include purchasing a 'starter kit,' paying to apply, or purchasing equipment or training.
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