Sr Software Engineer - Corp

About the Role

Key Responsibilities

• Design, develop, and deploy scalable, high performance data services, machine learning models to analyze large datasets, generate insights, and make predictions that support data-informed decision-making.
• Research, experiment, and build proof of concepts that solve business problems, scale them into functional MVPs and bring innovative concepts to life.
• Develop solutions and tackle ambiguous problems by framing issues, generating hypotheses, and offering recommendations that blend software engineering, analytics, and product expertise.
• Perform analysis using relevant tools (e.g., SQL, Python) and provide strategic contributions that drive business improvements.
• Document algorithms, methodologies, and findings thoroughly for transparency and reproducibility.
• Collaborate with cross-functional teams to architect and execute technically rigorous AI projects.
• Mentor and support other engineers, share knowledge and best practices on building data platforms around AI/Gen AI and machine learning.
• Work in a diverse, dynamic, collaborative, transparent, and inclusive environment where all ideas and opinions are valued.
• Support on-call activities for critical issues.

Requirements

• 5 years of relevant work experience. Bachelor's degree in Computer Science, Statistics, Mathematics, Physics, Economics, Engineering, or a related quantitative field.
• 3+ years of coding and software development experience, with proficiency in Golang, Java, C++, Python, or related languages.
• 3+ years of experience developing data services and data pipelines for business applications, with extensive hands-on experience in designing, building, evaluating, deploying, and monitoring data products end to end.
• Experience with databases, data warehousing, and ETL systems, including tools like Hadoop, Hive, Spark, Flink, BigQuery, Databricks, Snowflake, Fivetran, DBT, Airflow and data infrastructure services (AWS, GCP, Azure).
• Understanding of relevant statistical measures, such as confidence intervals, significance of error measurements, and the development and evaluation of datasets.
• Proven track record of analyzing data to uncover hidden patterns and conducting error/deviation analysis.
• Excellent written and verbal communication skills, with the ability to collaborate effectively in a distributed, cross-functional team environment.

Nice to Have

• Proficient in a range of machine learning algorithms, including random forests, linear and logistic regressions, gradient boosting, classification, GANs, and anomaly detection techniques.
• Experience in building machine translation and natural language processing systems.
• Ability to develop experimental and analytic plans for data modeling processes, establishing strong baselines, and accurately determining cause-and-effect relationships.
• Extensive experience with A/B testing setup and analysis.
• Experience with Reinforcement Learning in practical use cases.
• Experience in designing and implementing highly scalable, robust, and fault-tolerant services.
• Proficiency in training and fine-tuning models in large-scale environments (e.g., image, language, recommendation) with accelerators.
• Experience with CI/CD solutions in the context of MLOps and LLMOps, including automation with Infrastructure as Code (IaC) tools such as Terraform.
• Experience working with large-scale distributed systems and databases, particularly with very large datasets.
• Highly motivated to achieve results in a dynamic environment.
• Exceptional organizational skills and strong attention to detail.
• Comfort and effectiveness in a fast-paced, highly collaborative, and dynamic work environment.

Qualifications

• Bachelor's degree in a related quantitative field or equivalent experience.

Benefits & Perks

• Eligible to participate in Uber's bonus program.
• May be offered an equity award & other types of compensation.
• Eligible for various benefits as detailed at https://www.uber.com/careers/benefits.