Machine Learning Engineer

With a startup spirit and 115,000 + curious and courageous minds, we have the expertise to go deep with the world’s biggest brands—and we have fun doing it! We dream in digital, dare in reality, and reinvent the ways companies work to make an impact far bigger than just our bottom line. We’re harnessing the power of technology and humanity to create meaningful transformation that moves us forward in our pursuit of a world that works better for people. Now, we’re calling upon the thinkers and doers, those with a natural curiosity and a hunger to keep learning, keep growing. People who thrive on fearlessly experimenting, seizing opportunities, and pushing boundaries to turn our vision into reality. And as you help us create a better world, we will help you build your own intellectual firepower. Welcome to the relentless pursuit of better. Inviting applications for the role of ML Ops Engineer –India The position is based out of India and the focus to play a critical role in implementing machine learning projects in a production environment. The ideal candidate should have a strong background in data engineering, containerization, API development, log analysis, and metric generation. Key Responsibilities: Data Pipelines: Interpret and analyze data problems. To deal with huge data, have good understanding on data science and have worked on relational databases. Implement data pipelines, including the automatic collation of data from various sources, with a particular emphasis on DBeaver databases. - Containerization: Create containerization solutions for both data and machine learning models to ensure seamless deployment. Write computer programs and analyze large datasets to uncover answers to complex problems. Need to be comfortable writing code working in a variety of languages such as Python, and SQL. Ensure data quality and integrity through best practices and compliance to framework, architecture, and coding standards. Development: Design and develop an API that can ingest unseen data from CSV or Excel files, making real-time predictions using machine learning models. Generation: Establish a system to generate detailed logs of each machine learning model iteration on the data, enabling traceability and performance monitoring. Analysis and Metrics: Develop a system for log analysis, metrics generation, performance evaluation, and data anomaly detection. Use these insights to enhance model performance. Generation: Create detailed reports with metrics such as accuracy, sensitivity, recall, F1-score, and others to evaluate model performance and share results with stakeholders. Updates: Ensure that data and model updates can be seamlessly incorporated without affecting the functioning of existing model executions and real-time predictions. Proficiency: Implement Continuous Integration and Continuous Deployment (CI/CD) best practices to streamline the development, testing, and deployment of machine learning models. Management and Client Interaction: Interact with various client and internal teams within the organization, providing timely updates and collaborating throughout the different phases of model implementation. Communicate across a diverse audience across all levels of organization. Technical Skills Proficiency in Python and Jupyter Notebook for ML model development. Experience with containerization tools like Docker. Understanding of version control systems, especially Git, for model versioning. Familiarity with scripting languages such as Python, Bash, or PowerShell. Data pipeline development using Python, SQL, or Apache Spark. API development using Python and Flask, with experience in tools for creating and managing APIs like Postman. Jenkins, GitLab CI/CD to implement CI/CD methodologies . Qualifications Bachelor's or Master's degree in a relevant field (e.g., Computer Science, Data Science, or Engineering). 5-10 years of experience in the end-to-end implementation of machine learning models in a production environment. Strong knowledge of Python and data preprocessing. Familiarity with database technologies and SQL. Proficiency in CI/CD tools and log monitoring and analysis platforms. Excellent problem-solving and analytical skills. Project management and effective communication abilities. Industry-specific certifications or qualifications are a plus. Leadership Skills Strong organizational and leadership skills Passion for analytics, technology, and a keen learner to stay abreast on what is latest Ability to inspire and influence change in technology application Ability to work in diverse teams and with multiple stakeholders Conflict management and negotiation skills Skill gap identification and development of our global teams Excellent verbal and written communication skills 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 diversity and inclusion, respect and integrity, customer focus, and innovation. 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