We are looking for exceptional engineers to build systems for our very own employees and our customers. Our mission is to enhance Uber s corporate speed, reliability and worker happiness by building products, integrations and platforms. You will work closely with a highly capable team of engineers, data scientists, designers and product managers to ensure Ubers internal products and platforms are a powerful and innovative business advantage. The uSearch team is a part of BizTech that builds scalable, reliable, near realtime and robust enterprise integrations of a plethora of applications and services we build and use at Uber.
What you'll do:
Apply leading Models to solve business problems
- Use models from GPT-* to LLama-* to solve wide range of business problems from sales tech, employee productivity, coding and automation
- Build RAG frameworks
- Build Langchain modules
Model Development and Implementation:
- Design, develop, and deploy machine learning models to solve complex problems and improve user experiences, operational efficiency, or system performance.
- Utilize a variety of data sources, types, and structures to extract actionable insights through predictive analytics and data mining techniques.
Research and Innovation:
- Stay abreast of the latest developments in the field of machine learning and artificial intelligence. Evaluate emerging trends and technologies for potential adoption to maintain and expand competitive advantage.
- Lead research initiatives that test new algorithms, evaluate new methodologies, and explore innovative uses of data that can lead to scalable solutions.
Team Leadership and Development:
- Lead and mentor a team of machine learning engineers and data scientists. Ensure the continuous professional growth of team members through clear goal-setting, regular feedback, and development opportunities.
- Foster a collaborative and inclusive team environment that encourages innovation and iterative learning.
Cross-Functional Collaboration:
- Work closely with product management, software engineering, and data engineering teams to integrate machine learning models into larger software systems and product offerings.
- Partner with stakeholders across the organization to understand business needs and translate them into technical requirements and actionable machine learning projects.
Project Management:
- Oversee the full project lifecycle for multiple machine learning initiatives, from ideation and data collection to model development and deployment.
- Manage resources, timelines, and risks effectively, ensuring that projects meet their objectives and are delivered on schedule.
- Performance Monitoring and Model Optimization:
- Continuously monitor the performance of deployed models, identifying opportunities for improvement and optimization.
- Implement robust testing and validation strategies to ensure model accuracy and reliability over time.
What you'll Need:
- Experience in applying Gen-AI/LLM in production
- Managed at least a team 4+ engineers for end-to-end deliverables, for more than 2 years
- Education: Bachelors degree in Computer Science, Engineering, or a closely related field. Advanced degrees (masters or PhD) in fields that emphasize software engineering or machine learning are preferred.
- Professional Experience: At least 8 years of experience in software development with a proven track record in both software engineering and research or applied machine learning projects.
Technical Expertise:
- Expertise in programming using languages such as Python, Java, C++, or Scala.
- Proficient with modern software engineering tools and methodologies (eg, version control, CI/CD, agile development practices).
- Extensive experience with machine learning libraries and frameworks like TensorFlow, PyTorch, or Keras.
Data Proficiency:
- Strong capabilities in handling large datasets, with skills in SQL, NoSQL databases, data modeling, and ETL processes.
- Experience designing and implementing systems that collect, manage, and convert raw data into actionable insights through machine learning models.
Machine Learning Application Experience:
- Solid foundation in applying machine learning algorithms to real-world problems, optimizing algorithms for scalability and performance.
- Hands-on experience in building, scaling, and maintaining production-level machine learning models.
Employment Type: Full Time, Permanent
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