Summer 2024 Intern, Deep Learning for Computer Vision
Mountain View, CA, USA
Posted on Tuesday, January 30, 2024
Kodiak was founded in April 2018 to develop autonomous technology that carries freight forward—so people, partners, and the planet thrive. Navigating highway environments present vastly different challenges than urban streets. Kodiak’s experienced team has developed the industry’s most advanced technology stack purpose-built specifically for long-haul trucks. From our sensor fusion system that maximizes the value of every sensing modality to our unique lightweight mapping solution that allows our trucks to navigate ever-changing highway construction zones, our world-class team of industry pioneers is bringing the benefits of autonomy to the $800B a year trucking industry quickly, safely, and efficiently.
We are looking for a highly skilled Machine Learning Intern with a solid grasp of Computer Vision, to tackle real-world challenges in robotics. The perfect candidate for our team is someone who embodies a proactive, can-do mindset, tackling tasks with enthusiasm and persistence. We expect our interns to not only excel in their field but also to rapidly adapt and thrive in our fast-paced, innovative environment. This role is ideal for individuals eager to demonstrate their expertise and eager to grow in a cutting-edge technological setting.
In this role, you will:
- Design and implement state-of-the-art machine learning algorithms using robust, efficient C++ and Python code, ensuring high-quality testing and reliability.
- Lead the development of innovative deep neural networks to address key robotics problems, such as lane detection, object detection, sign recognition, and 3D perception.
- Collaborate with various sensor technologies like cameras, lidars, and radars to create and refine machine learning datasets, enhancing performance with growing data.
- Develop and manage automated training pipelines, ensuring seamless integration and efficiency in the machine learning process.
- Work within Kodiak's advanced software ecosystem, pushing the frontiers of existing autonomous systems through continuous innovation and development.
- Strong technical background. You are currently pursuing an MS or Ph.D. and have hands-on experience in designing and implementing deep neural networks; exceptional candidates pursuing a BS are considered. You are a skilled software engineer with experience in C++ and strong problem-solving skills.
- You are passionate about solving real-world robotics problems, and you have ideally worked on autonomous robots before. You ideally also have a strong knowledge of data processing pipelines for training ML models in the cloud.
- A team player. You take ownership and work with the team to deliver exceptional results. You are interested in the performance of the entire system across engineering disciplines.
- Ability to build and iterate quickly. You enjoy working fast and smart, and you are comfortable in the earlier stages of developing an algorithm from scratch.
- Hands-on. You are not only passionate about ML research but also experienced working with production machine learning pipelines, from dataset collection and labeling to training and validation.
- Great communicator. You have experience writing clear, concise, and detailed documentation. You can enable your colleagues to leverage the ML models resulting from your work in their algorithms and systems.
Internship Program Details:
- Start Date: May/June 2024.
- Our internship program is 12-16 weeks; the end date is flexible based on individual needs.
- Location: Mountain View, CA.
- Housing: interns are responsible for housing.
What we offer:
- A fast paced environment where we work with talented, committed and supportive teammates.
- Competitive pay.
- Excellent medical, dental and vision benefits. A beautiful facility in Mountain View.
- We love our dogs, so we are a dog friendly office!
- Free catered lunch.
The monthly range for this intern position is $9,166-$10,000 . Our salary ranges are determined by role, level and location. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position across all US locations. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. We can share more about the specific salary range for your job level during the hiring process. Please note that the compensation details listed above are base salary only and do not include bonus, equity, or benefits.
At Kodiak, we strive to build a diverse community working towards our common company goals in a safe and collaborative environment where harassment of any kind is strictly prohibited. Kodiak is committed to equal opportunity employment regardless of race, ethnicity, religion, gender identity, sexual orientation, age, disability, or veteran status, or any other basis protected by applicable law.
In alignment with its business operations, Kodiak adheres to all relevant U.S. national security statutes, regulations, and administrative prerequisites. These statutes may impose limitations on Kodiak's capacity to engage specific individuals in particular roles based on various national security-related criteria. Consequently, the eligibility for this position may hinge on Kodiak's verification of a candidate's residence, U.S. person status, and/or citizenship status. In accordance with these statutes , Kodiak may find it necessary to secure a U.S. government export license before disseminating its technologies to specific individuals. Should Kodiak determine that a candidate's residence, U.S. person status, and/or citizenship status necessitate a license, prohibit the candidate from assuming this position, or otherwise fall under national security-related restrictions, Kodiak explicitly retains the right to either assess the candidate for an alternative position unaffected by such restrictions, under terms and conditions set forth at Kodiak's sole discretion, or, as an alternative, opt not to proceed with the candidate's application.