Search for Staff Machine Learning Engineer roles in New York, focusing on full-time positions, with experience in deep learning and optimization methods. I'm looking for roles that offer a salary of at least $223,000 and require leadership experience.

Okay, I've searched for Staff Machine Learning Engineer roles in New York, specifically full-time positions that include expertise in deep learning and optimization methods. I’ve only included roles that offer a salary of at least $223,000 and require leadership experience. I found 35 positions for you to explore.

Staff Machine Learning Engineer

New York, NY

Full Time

deep learning

optimization

$223000+

Senior

Can you help me to analyze the job description and company culture?

Sure. Here's the analysis:

Job Analysis:

The Staff Machine Learning Engineer position within Uber's Delivery Marketplace serves a critical function in optimizing the operations of Uber's delivery services, which have expanded from ridesharing to include food and grocery delivery. At the core of this role is the responsibility to lead the design and development of advanced machine learning solutions that impact real-time decision-making processes, such as dispatch and delivery time predictions. Success in this role involves not just technical proficiency in machine learning and software engineering but also a strategic vision to balance business objectives with user experience. Candidates will face challenges such as complex problem-solving within a rapidly evolving marketplace, requiring them to deploy algorithms that handle vast datasets, enhance efficiency, and contribute to the organization’s bottom line. The role necessitates strong leadership capabilities as the engineer will mentor junior team members, guiding them through the intricacies of model development and implementation, thereby shaping the future of Uber's delivery operations. Overall, success in this role means delivering innovative solutions that improve operational efficiency while also creating a 'magical' user experience.

Company Analysis:

Uber occupies a unique and disruptive space in the tech-driven logistics and mobility industry, known for its relentless focus on innovation and reimagination of how mobility is perceived and utilized. This fast-paced and rapidly evolving environment suggests that adaptability and forward-thinking will be crucial traits for anyone stepping into the Staff Machine Learning Engineer role. The company’s culture reflects a 'go-getter' mentality, where collaboration, creativity, and the willingness to take risks are highly valued. As a member of a cross-functional team, this role involves significant collaboration with product managers, data scientists, and engineers, potentially offering substantial visibility to leadership and a direct impact on decision-making processes. This strategic alignment positions the role as pivotal to Uber’s growth ambitions, especially in expanding its delivery marketplace, indicating that candidates should be prepared not only to execute tasks but also to innovate solutions that drive the company’s objectives forward. The successful engineer will play a key role in enabling Uber to enhance user experience while optimizing operational efficiency, underscoring the direct correlation between individual contributions and broader business goals.

Mock up some interview questions based on the job description.

Absolutely. Here are some mock interview questions that could come up:

Tell me about a time when you had to lead a project that involved solving a complex problem with machine learning. What was your approach?
Can you describe an instance where you had to mentor a junior engineer? What strategies did you use to support their development?
Share an experience where you faced ambiguity during a project. How did you navigate through it?
What has been your experience with large-scale machine learning solutions? Can you give a specific example of a project you worked on?
How would you approach optimizing real-time operations in a delivery marketplace like Uber's?
What techniques would you employ to build a reinforcement learning model for dispatch optimization?
Explain how you would balance user experience and business objectives when developing machine learning algorithms.
Imagine you are faced with a sudden drop in delivery efficiency metrics. How would you investigate and resolve this issue?
If you were to lead a team to develop a forecasting model, what key metrics would you prioritize, and why?
Why are you interested in working at Uber specifically, especially in the Delivery Marketplace?
How do you think your previous experiences align with Uber's mission to enhance movement and delivery services?
What aspects of our company culture resonate with you, and how would you contribute to that culture?
What questions do you have about our machine learning infrastructure or the current challenges the Delivery Marketplace is facing?
How do you envision the future of delivery services and the role machine learning will play in that evolution?

Job Details

Overview Company

Staff Machine Learning Engineer

$223k/y-$248k/y

Uber

3 days ago

Highlight

OnsiteFull-time5+ yearsSenior

Summary

Uber is seeking a Staff Machine Learning Engineer - Delivery Marketplace to join their team in New York, NY. The role involves leading the development of optimization solutions using real-time and machine learning signals to enhance Uber's delivery operations.

About the Role

As a Staff Machine Learning Engineer, you will lead the design and development of machine learning solutions that optimize real-time operations across Uber's Delivery Marketplace. You will build advanced ML models using techniques such as reinforcement learning, deep learning, and optimization methods to improve efficiency and user experience. You will mentor a team of MLEs, collaborate with cross-functional teams, and solve complex problems using state-of-the-art forecasting and prediction models.

About You

Required:

PhD or equivalent in Computer Science, Engineering, Mathematics or related field AND 2-years full-time Software Engineering work experience OR 5-years full-time Software Engineering work experience, WHICH INCLUDES 3-years total technical software engineering experience in areas such as programming languages, large-scale training, modern machine learning algorithms, and experience with SQL and database systems.
Experience in the development, training, productionization and monitoring of ML solutions at scale.

Preferred:

Experience in a technical leadership role and mentoring junior engineers.
Experience in modern deep learning architectures and probabilistic models.
Experience in optimization (RL / Bayes / Bandits) and online learning.
Experience in causal inference/personalization/ranking.

Benefits

Base salary range of $223k–$248k for New York, NY-based roles.
Eligibility to participate in Uber's bonus program.
Potential equity award and other types of compensation.
Various benefits as detailed on Uber's careers page.

Uber

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.

New York, NY