SUMMARY

We are seeking a talented Machine Learning Engineer to join our Global ML Ops team, driving the development of AI-driven solutions that will shape the future of our company. You design and develop scalable ML solutions including recommendation, personalization, classification, predictive models, generative AI and conversational AI. Your goal will be to unify and optimize existing and perspective solutions, proof of concepts, experiments, deploy and monitor production systems. With the strong background in Machine Learning and software engineering you will help to bring insights and identify additional opportunities in ML Ops.
The ideal candidate will have a solid background in software development with proficiency in multiple programming ecosystems (including Python, JavaScript and React) and experience in building scalable, high-performance applications.

In this role, you’ll have the chance to build and maintain innovative new experiences for our internal and customer-facing web applications. You’ll continually learn, grow, and expand your knowledge. At the same time, you’ll support others’ learning experiences, acting as a mentor and a resource for others both inside and outside of your team. You’ll collaborate with our talented Product and Engineering teams, as well as other parts of organization, to deliver great products. You’ll utilize best practices for architecture, implementation, testing, monitoring, logging, and deployments. You’ll also take on ad-hoc projects as they arise and always be willing to support your team where they need you. Lastly, you’ll communicate and exchange accurate information with others via telephone or internet video applications.

PRIMARY RESPONSIBILITIES

• Develop and implement advanced ML models, such as graph neural networks and deep learning models, to solve critical business problems related to recommendation of our products, personalizing product experiences including UI flows, and optimizing the lifecycle of the customers on the platform.
• Design and deploy scalable generative AI solutions as part of the ecosystem.
• Design and deploy scalable ML/AI solutions that enhance the ability to provide a seamless customer experience.
• Communicate complex concepts and the results of models and analyses to both technical and non-technical audiences, influencing partners and customers with your insights and expertise.
• Develop code in React/JS to add new features our existing products.
• Drive the design discussions, code reviews and the daily stand-ups.
• Contribute to the detailed design and architecture of the backend API services and the front-end applications.
• Partner with the Product team in understanding the requirement and building the backlog for new initiatives.
• Stay on top of technical implementation of all the initiatives and work with the engineering leadership in identifying and mitigating the risks impacting the delivery.
• Partner with QA and provide the required support for addressing the bugs raised during regression and functional testing.
• Work in an Agile environment with daily stand-ups and 2-week sprints

REQUIRED KNOWLEDGE/SKILLS/ABILITIES

• Master’s degree or equivalent experience in a quantitative field (Computer Science, Mathematics, Statistics, Engineering, Artificial Intelligence, etc.) with 8+ yrs. of relevant industry experience or PhD with 3+ yrs. of relevant industry experience
• Proficient in Programming languages such as Python, SQL, JavaScript with 9+ yrs
• Experience in front-end development, working with React a big plus.
• Experience in any one of Recommendation, Ranking, Product and Marketing domains a big plus.
• Experience in Machine Learning Operations, DevOps – an advantage.
• Familiarity in relevant machine learning frameworks and packages such as Tensorflow and PyTorch. GCP/AWS and big data experience – an advantage
• Experience leading ML projects and great track record delivering solutions with attention to detail and efficiency.
• Experience shipping Realtime models a big plus.
• Fluent spoken and written English communication with business and engineering partners to exchange requirements, explain solution methodologies, and influence with insights.
• Strong communication skills – an advantage.