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Machine Learning Engineer

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Uber

1mo ago

Applications are closed

  • Job
    Full-time
    Mid Level
  • Engineering
  • Sunnyvale, +2

Requirements

  • Basic Qualifications:
  • Bachelor's or Master's in Computer Science, Statistics, or a related field.
  • Experience with a strong focus on machine learning and optimization.
  • Experience with ML packages such as Tensorflow, PyTorch, JAX, and Scikit-Learn.
  • Solid understanding of statistical analysis and feature engineering techniques.
  • Excellent communication and collaboration skills.
  • Ability to work independently and take ownership of projects.
  • Experience using SQL in a production environment.
  • Experience in experimental design and analysis, exploratory data analysis, and statistical analysis.
  • Experience with dashboarding and using data visualization tools.
  • Experience using statistical methodologies such as sampling, statistical estimates, descriptive statistics, or similar.
  • Preferred Qualifications:
  • Experience in the Search and Recommendations Field.
  • Experience in Query Understanding / Ranking or solving customer problems with NLP.
  • Experience developing end-to-end GenAI products

Responsibilities

  • Design, develop, and productionize machine learning (ML) solutions in : Search and Discovery , GenAI, QU/Ranking , MOO optimizations.
  • Productionize and deploy these models for real-world applications.
  • Design and analyze experiments using a combination of data analysis/statistical analysis to lead the team to a reasonable inference.
  • Review code and designs of teammates, providing constructive feedback.
  • Collaborate with Product and cross-functional teams to brainstorm new solutions and iterate on the product.

FAQs

What is the primary role of the Machine Learning Engineer in the Uber Eats Search and Discovery Team?**

The primary role of the Machine Learning Engineer is to enhance the search experience for millions of Uber Eats users worldwide by leveraging expertise in data analysis, machine learning, and engineering to drive insights and optimize search algorithms. **Question: What are the key responsibilities of the Machine Learning Engineer?** **Answer:** Key responsibilities include designing, developing, and productionizing machine learning solutions for Search and Discovery, GenAI, query understanding/ranking, and MOO optimizations; deploying models for real-world applications; designing and analyzing experiments; reviewing code and designs; and collaborating with product and cross-functional teams. **Question: What educational qualifications are preferred for this position?** **Answer:** A Bachelor's or Master's degree in Computer Science, Statistics, or a related field is preferred. **Question: What experience is essential for a candidate applying for this role?** **Answer:** Candidates should have experience with machine learning and optimization, as well as familiarity with ML packages such as Tensorflow, PyTorch, JAX, and Scikit-Learn. Additionally, solid understanding and experience in statistical analysis, feature engineering techniques, SQL in a production environment, experimental design, and the search and recommendations field are essential. **Question: What soft skills are expected from candidates for this Machine Learning Engineer position?** **Answer:** Excellent communication and collaboration skills, the ability to work independently and take ownership of projects, and a constructive approach to providing feedback on teammates’ code and design are expected. **Question: Is experience in natural language processing (NLP) relevant for this role?** **Answer:** Yes, experience in query understanding/ranking or solving customer problems with NLP is relevant and preferred for this position. **Question: What does the base salary range for this position entail?** **Answer:** The base salary range for this role is USD $158,000 to USD $175,500 per year, depending on the location, including San Francisco, Seattle, and Sunnyvale. **Question: Are there additional compensation opportunities besides the base salary?** **Answer:** Yes, individuals will be eligible to participate in Uber's bonus program, may be offered an equity award, and can expect other types of compensation and benefits. **Question: Where can I find more details about the benefits offered with this position?** **Answer:** More details about the benefits offered can be found on Uber's careers page at the following link: https://www.uber.com/careers/benefits. **Question: What types of projects will the Machine Learning Engineer work on?** **Answer:** The Machine Learning Engineer will work on projects related to search and discovery algorithms, generative AI products, query understanding/ranking, and various optimization tasks to improve the overall user experience.

Uber

We reimagine the way the world moves for the better.

Technology
Industry
10,001+
Employees
2009
Founded Year

Mission & Purpose

We are Uber. The go-getters. The kind of people who are relentless about our mission to help people go anywhere and get anything and earn their way. Movement is what we power. It’s our lifeblood. It runs through our veins. It’s what gets us out of bed each morning. It pushes us to constantly reimagine how we can move better. For you. For all the places you want to go. For all the things you want to get. For all the ways you want to earn. Across the entire world. In real time. At the incredible speed of now. The idea for Uber was born on a snowy night in Paris in 2008, and ever since then our DNA of reimagination and reinvention carries on. We’ve grown into a global platform powering flexible earnings and the movement of people and things in ever expanding ways. We’ve gone from connecting rides on 4 wheels to 2 wheels to 18-wheel freight deliveries. From takeout meals to daily essentials to prescription drugs to just about anything you need at any time and earning your way. From drivers with background checks to real-time verification, safety is a top priority every single day. At Uber, the pursuit of reimagination is never finished, never stops, and is always just beginning.

Culture & Values

  • Go get it

    Bring the mindset of a champion. Our ambition is what drives us to achieve our mission. How we define a champion mindset isn’t based on how we perform on our best days, it’s how we respond on the worst days. We hustle, embrace the grind, overcome adversity, and play to win for the people we serve. Because it matters.

  • Trip obsessed

    Make magic in the marketplace. The trip is where the marketplace comes to life. The earner, rider, eater, carrier and merchant are the people who connect in our marketplace - and we see every side. This requires judgment to make difficult trade-offs, blending algorithms with human ingenuity, and the ability to create simplicity from complexity. When we get the balance right for everyone, Uber magic happens.

  • Build with heart

    We care. We work at Uber because our products profoundly affect lives and we care deeply about our impact. Putting ourselves in the shoes of the people who connect in our marketplace helps us build better products that positively impact our communities and partners. Our care drives us to perfect our craft.

  • Stand for safety

    Safety never stops. We embed safety into everything we do. Our relentless pursuit to make Uber safer for everyone using our platform will continue to make us an industry leader for safety. We know the work of safety never stops, yet we can and will challenge ourselves to always be better for the communities we serve.

  • See the forest and the trees

    Know the details that matter. Building for the intersection of the physical and digital worlds at global scale requires seeing the big picture and the details. Knowing the important details can change the approach, and small improvements can compound into enormous impact over time.

  • One Uber

    Bet on something bigger. It’s powerful to be a part of something bigger than any one of us, or any one team. That’s why we work together to do what’s best for Uber, not the individual or team. We actively support our teammates, and they support us - especially when we hit the inevitable bumps in the road. We say what we mean, disagree and commit, and celebrate our progress, together.

  • Great minds don't think alike

    Diversity makes us stronger. We seek out diversity. Diversity of ideas. Identity. Ethnicity. Experience. Education. The more diverse we become, the more we can adapt and ultimately achieve our mission. When we reflect the incredible diversity of the people who connect on our platform, we make better decisions that benefit the world.

Benefits

  • Comprehensive Healthcare

  • Flexible Work

  • Uniquely Uber

  • Health & Wellness