Senior Machine Learning Engineer

Job Description

Title: Senior Machine Learning Engineer Location: Gurgaon, IN Type: (Hybrid, In-Office) Job Description Who We Are: Fareportal is a travel technology company powering a next-generation travel concierge service. Utilizing its innovative technology and company owned and operated global contact centres, Fareportal has built strong industry partnerships providing customers access to over 500 airlines, a million lodgings, and hundreds of car rental companies around the globe. With a portfolio of consumer travel brands including CheapOair and OneTravel, Fareportal enables consumers to book-online, on mobile apps for iOS and Android, by phone, or live chat. Fareportal provides its airline partners with access to a broad customer base that books high-yielding international travel and add-on ancillaries. HIGHLIGHTS : Fareportal is the number 1 privately held online travel company in flight volume. Fareportal partners with over 500 airlines, 1 million lodgings, and hundreds of car rental companies worldwide. 2019 annual sales exceeded $5 billion. Fareportal sees over 150 million unique visitors annually to our desktop and mobile sites. Fareportal, with its global workforce of over 2,600 employees, is strategically positioned with 9 offices in 6 countries and headquartered in New York City. What We Do Our Machine Learning team is at the forefront of developing state-of-the-art models and solutions that drive key business decisions, improve customer experiences, and streamline operations. We work on diverse projects, from personalized recommendations and predictive modelling to call analytics and business forecasting, using cutting-edge technology and data-driven insights. Our department is unique in its end-to-end approach to problem-solving, focusing on innovation, collaboration, and impactful results. As a Senior Machine Learning Engineer, you will play a crucial role in the complete lifecycle of our Machine Learning projects. You will: - Engage with stakeholders to gather and refine requirements. - Perform exploratory data analysis (EDA) and manipulate data using SQL and NoSQL databases. - Engineer and select features, ensuring optimal model performance. - Train, test, and fine-tune models using advanced algorithms and methodologies. - Deploy models into production environments using frameworks like Docker, Kubernetes, and Rest APIs. - Monitor and evaluate model performance, including A/B testing and continuous improvement. - Collaborate with cross-functional teams, ensuring seamless integration and communication throughout the project lifecycle. In this Role You Will Get To - Work within a dynamic and talented team of engineers and data scientists to build scalable Machine Learning solutions that impact thousands of users daily. - Develop, deploy, and maintain Machine Learning models that address complex business challenges and enhance customer engagement. - Participate in brainstorming sessions, technical design discussions, and collaborate with product managers, data engineers, and other stakeholders to ensure alignment and success. - Explore and implement new technologies, including cloud-based (AWS, Azure) and on-prem systems, to optimize and enhance ML model performance. - Conduct rigorous testing and monitoring to ensure the reliability and accuracy of models. Who You Are Must-Haves: - Strong communication skills, capable of translating technical concepts into actionable business insights. - Proven experience (2-4 years) as a Data Scientist, Machine Learning Engineer, or in a similar role. - Proficient in SQL querying for data extraction and manipulation. - Experience with high volume structured data, including data manipulation, exploratory data analysis (EDA), and data modelling. - Strong proficiency in Python programming and familiarity with Rest API frameworks for seamless model integration. - Demonstrated ability to build and deploy at least 3-5 ML models in production environments. - Hands-on experience with Regression, Classification, Recommendation algorithms, and Neural Networks. - Expertise in relevant ML libraries such as CatBoost, XGBoost, LightGBM, Scikit-learn, TensorFlow, and PyTorch. - Knowledge of containerization technologies (e.g., Docker, Kubernetes) and virtual machines (VMs). - Familiarity with cloud (AWS/Azure) and on-prem data systems. - Bachelors in computer science, or a related field; a Master's degree is a plus. Good-to-Haves: - Experience working with distributed data processing frameworks like PySpark. - Experience working with Natural Language Processing (NLP) and Large Language Models (LLMs). - Familiarity with MLOps platforms such as MLFlow and Kubeflow. - Prior experience with A/B testing methodologies. - Advanced skills in data visualization tools like Tableau or Power BI. Disclaimer This job description is not designed to cover or contain a comprehensive listing of activities, duties or responsibilities that are required of the employee. Fareportal reserves the right to change the job duties, responsibilities, expectations, or requirements posted here at any time at the Company's sole discretion, with or without notice.