Sr Software Engineer

Delivers complete solutions spanning all phases of the Software Development Lifecycle (SDLC) (design, implementation, testing, delivery and operations), based on definitions from more senior roles. Advises immediate management on project-level issues Guides junior engineers Operates with little day-to-day supervision, making technical decisions based on knowledge of internal conventions and industry best practices Applies knowledge of technical best practices in making decisions Design and develop highly scalable and efficient platform that enables data scientists to build, deploy, and monitor machine learning solutions end-to-end. Ensure high code quality, performance, and reliability through rigorous testing, code reviews, and adherence to software development best practices. Drive innovation by researching and incorporating state-of-the-art machine learning techniques, tools, and frameworks into the platform. Effective communication, listening, interpersonal, influencing, and alignment driving skills; able to convey important messages in a clear and compelling manner. Mentor team members, provide technical guidance, and foster a culture of collaboration, innovation, and continuous learning. Explore state-of-the-art deep learning techniques and Partner with data science and domain engineering teams to support the business transformation through AI. Develop trusted partnership with business, product, data scientists and architecture leaders to drive optimized platform product delivery 3+ years relevant experience and a Bachelor's degree OR Any equivalent combination of education and experience. We are hiring talented and creative ML engineer for AIML platform team based in San Jose CA, you will be customer-centric, strategic & analytical in decision making and laser-focused on executing at scale. You thrive on the challenge of building and optimizing platforms at scale, are deeply passionate about leveraging cutting-edge technologies, and are dedicated to innovation and market success. You will have a chance to work on solving real world problems and gain practical experience in end to end Machine Learning life cycle. You will design, build, and optimize the platform for ML pipeline and data infrastructure. Ability to influence at all levels of the organization and across multiple domains. Ability to lead complex technical and data science discussions and engagements that involve multiple personas including data scientists, data engineers, analysts and developers. Solid track record of over-achieving engineering and platform delivery and scaling targets in high volume, innovative and fast-paced high-pressure environment; proven results in delivery on platform products. Masters / bachelor's in computer science, Computer engineering, Machine Learning, Data Mining, Information Systems, or related disciplines, with technical expertise in one or more of the above-mentioned areas or equivalent practical experience. Strong proficiency in machine learning concepts, algorithms, and techniques, with hands-on experience in developing and deploying machine learning models. Expertise in programming languages such as Python, Go, Java, and proficiency in machine learning libraries/frameworks such as TensorFlow, PyTorch, scikit-learn, etc. Stay up-to-date with the latest advancements in AI/ML technology and industry trends, and leverage this knowledge to enhance the platform's capabilities. Experience with cloud platforms (e.g., AWS, Azure, GCP) and containerization technologies (e.g., Docker, Kubernetes). Strong communication, listening, interpersonal, influencing, and alignment driving skills; able to convey important messages in a clear and compelling manner Demonstrated leadership abilities, including the ability to inspire, mentor, and empower team members to achieve their full potential. Experience with Jupyter Notebook, Kubeflow, Airflow, Argo, GPU and HPC Experience building ML infrastructure or MLOps platforms and Bigdata platforms technologies such as Hadoop, BigQuery, Spark, Hive and HDFS