Senior ML Engineer

The people at UiPath believe in the transformative power of automation to change how the world works. We’re committed to creating category-leading enterprise software that unleashes that power.

To make that happen, we need people who are curious, self-propelled, generous, and genuine. People who love being part of a fast-moving, fast-thinking growth company. And people who care—about each other, about UiPath, and about our larger purpose.

Could that be you?

UiPath Inc. is seeking a highly skilled and experienced Senior Software Engineer to join our rapidly growing AI & Research group. The ideal candidate will have a strong background in software engineering and machine learning as well as a passion for staying up to date with the latest advances in these fields. They will play a crucial role for designing, implementing, and optimizing cutting-edge machine learning systems and help lead our team to success.

1. Develop and implement machine learning infrastructure for advanced machine learning models and systems for various business applications, ensuring high performance and scalability.
2. Collaborate with cross-functional teams, including data scientists, product managers, and software engineers, to define requirements and deliver end-to-end machine learning solutions.
3. Provide technical leadership and mentorship to a team of software engineers, fostering a culture of collaboration, innovation, and continuous learning.
4. Drive the adoption of best practices for software development, testing, and deployment, as well as MLOps and Cloud computing principles.
5. Stay current with industry trends, emerging technologies, and relevant research in the field of machine learning.

1. Bachelor's or Master's degree in Computer Science, Engineering, or a related field. Strong fundamentals with a solid understanding of data structures and algorithms.
2. 8+ years of software engineering experience.
3. 3+ years of experience in machine learning is a plus, including experience with popular machine learning frameworks (e.g., TensorFlow, PyTorch) and libraries (e.g., Pandas, Numpy).
4. Strong knowledge of cloud computing platforms (e.g., AWS, Azure, GCP) and experience building cloud-based machine learning systems.
5. Familiarity with MLOps principles and practices, including CI/CD, model versioning, monitoring, and deployment.
6. Excellent problem-solving and analytical skills.
7. Strong communication and interpersonal skills, with the ability to work effectively in a collaborative team environment.

Maybe you don’t tick all the boxes above— but still think you’d be great for the job? Go ahead, apply anyway. Because we know that experience comes in all shapes and sizes—and passion can’t be learned.

Many of our roles allow for flexibility in when and where work gets done. Depending on the needs of the business and the role, the number of hybrid, office-based and remote workers will vary from team to team. Applications are assessed on a rolling basis and there is no fixed deadline for this requisition. The application window may change depending on the volume of applications received or may close immediately if a qualified candidate is selected.

We value a range of diverse backgrounds, experiences and ideas. We pride ourselves on our diversity and inclusive workplace that provides equal opportunities to all persons regardless of age, race, color, religion, sex, sexual orientation, gender identity and expression, national origin, disability, neurodiversity, military and/or veteran status, or any other protected classes. Additionally, UiPath provides reasonable accommodations for candidates on request and respects applicants' privacy rights. To review these and other legal disclosures, visit our privacy policy.

The anticipated base salary range for this position is between $200,200 and $289,900. Base salary ranges may vary by geographic location and relevant experience, education, certifications, and seniority as compared to others doing substantially similar work. There is no guarantee an offer will be at the top of the posted range based on the salary analysis.