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Senior Machine Learning Engineer - Machine Learning Infrastructure

Senior Machine Learning Engineer - Machine Learning Infrastructure

Location: based in NYC or US remote


About Flip.shop:

Welcome to Flip.shop, where innovation meets the social commerce revolution! Fresh off our Series C funding round, we've raised $144 million, propelling our valuation to an impressive $1.05 billion. We’re redefining the shopping experience by giving consumers a voice in a space dominated by tech giants. Join us on this exhilarating journey where your technical skills will play a pivotal role in shaping the future of social commerce!


Why Join Us?

At Flip.shop, you’ll be at the forefront of innovation in social commerce. This isn’t just a job—it’s a chance to build infrastructure that empowers our AI-driven platform to scale and deliver personalized shopping experiences. You will have the opportunity to directly partner, work with and learn from the very best engineers and scientists who joined us from some of the leading big-tech companies! 

If you thrive in a fast-paced, collaborative environment where you can develop high-performance systems, we want to hear from you!


Role Overview:

We are seeking a Senior Machine Learning Engineer - Machine Learning Infrastructure to design, build, and optimize the infrastructure that powers our machine learning systems. You’ll ensure the efficient deployment, scaling, and monitoring of machine learning models, and will help streamline the development lifecycle. This role offers the opportunity to create scalable, production-level systems that support real-time recommendations and drive business growth.


Responsibilities:
  • Infrastructure Development: Design and implement scalable infrastructure for deploying, monitoring, and maintaining machine learning models in production environments. Design and implement machine learning systems for feeds, ads, and search ranking models.
  • Training Infrastructure: Optimize the serving and training infrastructure of machine learning models.
  • Model Training: Enhance the workflow for model training and serving, data pipelines, storage systems, and resource management within multi-tenancy machine learning systems.
  • Tooling & Automation: Build tools to automate workflows for model training, testing, and deployment, ensuring that machine learning models can move quickly from development to production.
  • Performance Optimization: Ensure the infrastructure supports high-performance model inference at scale, with a focus on minimizing latency and maximizing throughput.
  • Collaboration: Work closely with data scientists, machine learning engineers, and DevOps teams to create seamless integration between development and production environments.
  • Monitoring & Maintenance: Build robust monitoring systems to track model performance and infrastructure health, ensuring reliability and uptime of machine learning services.
  • Security & Compliance: Implement best practices in infrastructure security, data privacy, and compliance, particularly when handling sensitive user data.


Requirements:
  • Education: Bachelor's degree or higher in Computer Science or a related field, with 3+ years of experience in building scalable systems.
  • Technical Skills: Proficiency in one or two programming languages (C/C++, Golang) within a Linux environment.
  • Solid understanding of GPU hardware architecture, GPU software stack (CUDA, cuDNN), and experience in GPU performance analysis.
  • Experience in deep model inference/training, debugging, and tuning.
  • ML Workflow Knowledge: Familiarity with mainstream machine learning frameworks (e.g., TensorFlow, PyTorch, MxNet).
  • Familiarity with MLOps practices.
  • Experience with big data frameworks (e.g., Spark, Hadoop, Flink) and resource management and task scheduling for large-scale distributed systems.
  • Open-source: Experience in using or designing open-source machine learning lifecycle management systems like TFX.


Key Skills
  • Excellent logical analysis and problem-solving skills with the ability to abstract and decompose complex business logic.
  • Strong sense of responsibility, good learning ability, communication skills, and self-motivation, with the ability to respond and act quickly.
  • Good working document habits, with timely writing and updating of workflow and technical documentation.


Why You’ll Love Working Here:

At Flip.shop, you’ll have the opportunity to build the backbone of our AI-driven platform, working on cutting-edge infrastructure that powers personalized shopping experiences for millions of users. Your work will directly contribute to scaling our machine learning systems, ensuring they run efficiently in a high-performance production environment. This is your chance to have a lasting impact and help Flip.shop shape the future of social commerce.


Ready to Build the Future?

If you're passionate about building scalable infrastructure and driving innovation in machine learning at scale, join us at Flip.shop! Let’s redefine the future of online shopping together.


Compensation & Benefits:

Base salary and total compensation will vary based on factors including but not limited to location, experience, and performance. Please note the base salary is just one component of the company’s total rewards package for exempt employees. Other rewards may include equity, bonuses, long term incentives, a PTO policy, and other progressive benefits.

Average salary estimate

$130000 / YEARLY (est.)
min
max
$100000K
$160000K

If an employer mentions a salary or salary range on their job, we display it as an "Employer Estimate". If a job has no salary data, Rise displays an estimate if available.

What You Should Know About Senior Machine Learning Engineer - Machine Learning Infrastructure, Flip

At Flip.shop, we are on a mission to revolutionize social commerce and we’re looking for a talented Senior Machine Learning Engineer - Machine Learning Infrastructure to join our innovative team. This remote opportunity lets you shape the future of shopping by developing top-notch infrastructure that powers our machine learning systems. You will be integral in designing and implementing scalable solutions for deploying, monitoring, and optimizing machine learning models in production. With your expertise, you will work collaboratively with some of the best engineers from leading tech companies, driving initiatives that help our AI-driven platform deliver personalized shopping experiences to millions. Your role will involve enhancing model training workflows, building automation tools, optimizing system performance, and ensuring the security of our infrastructure while maintaining compliance with data privacy regulations. As a key player in a fast-paced environment, you’ll also get to share your insights and work closely with cross-functional teams including data scientists and DevOps specialists. If you're ready to combine your technical skills with a passion for innovation, join us at Flip.shop and be a part of this thrilling journey towards reshaping how consumers shop online!

Frequently Asked Questions (FAQs) for Senior Machine Learning Engineer - Machine Learning Infrastructure Role at Flip
What are the responsibilities of a Senior Machine Learning Engineer at Flip.shop?

As a Senior Machine Learning Engineer - Machine Learning Infrastructure at Flip.shop, your main responsibilities will revolve around designing and building scalable infrastructure to support machine learning models. You will work on deploying, monitoring, and maintaining these models, optimizing workflows for model training, and enhancing tooling to automate processes. Collaboration with data scientists and DevOps teams to ensure seamless integration also forms a critical part of your role.

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What qualifications do I need to apply for the Senior Machine Learning Engineer position at Flip.shop?

To qualify for the Senior Machine Learning Engineer - Machine Learning Infrastructure role at Flip.shop, you should have a Bachelor's degree in Computer Science or a related field, alongside at least 3 years of experience in building scalable systems. Proficiency in programming languages like C/C++ or Golang, a solid understanding of GPU architectures, and familiarity with machine learning frameworks such as TensorFlow and PyTorch are essential.

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What technical skills are required for the Senior Machine Learning Engineer role at Flip.shop?

Candidates aspiring for the Senior Machine Learning Engineer - Machine Learning Infrastructure position at Flip.shop should possess proficiency in programming languages (C/C++, Golang) and have a solid understanding of the GPU software stack (CUDA, cuDNN). Experience with deep model inference, MLOps practices, and big data frameworks will also be valuable in this role as you build high-performance production systems.

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How does collaboration work in the Senior Machine Learning Engineer role at Flip.shop?

In your role as a Senior Machine Learning Engineer - Machine Learning Infrastructure at Flip.shop, you will closely collaborate with data scientists, other machine learning engineers, and DevOps teams. This interdepartmental teamwork is crucial for integrating development and production environments to streamline workflows and enhance system performance.

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What is the company culture like for Senior Machine Learning Engineers at Flip.shop?

Flip.shop fosters a collaborative and innovative environment for all its team members, including Senior Machine Learning Engineers. The culture is fast-paced, encouraging continuous learning and development. You will work alongside top engineers, engage in exciting projects, and have the opportunity to influence the future of social commerce through your contributions.

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Common Interview Questions for Senior Machine Learning Engineer - Machine Learning Infrastructure
Can you explain your experience with building scalable machine learning systems?

It’s crucial to provide specific examples of projects where you’ve designed scalable systems, detailing the architecture, technologies used, and outcomes. Highlighting challenges faced and how you overcame them will showcase your problem-solving skills.

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What programming languages are you proficient in, and how have you applied them in machine learning projects?

Clearly state your experience with relevant programming languages like C/C++ and Golang. Illustrate how you’ve utilized these languages in developing machine learning models or infrastructure to reinforce your technical capabilities.

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How do you ensure the security and compliance of machine learning models?

Discuss best practices you follow for data security, including encryption and access controls. Share any experiences or systems you’ve implemented to ensure compliance with data privacy regulations, particularly when handling sensitive user data.

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Describe a time you collaborated with data scientists to enhance a machine learning project.

Provide an example of how you worked with data scientists, emphasizing communication and teamwork. Detail how your technical insights contributed to the success of the project and fostered a collaborative environment.

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What strategies do you use for optimizing machine learning model performance?

Discuss the techniques you apply for performance optimization, such as profiling, benchmarking, and adjusting model parameters. Sharing specific tools or frameworks you've used can also demonstrate your hands-on experience.

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How do you approach debugging machine learning systems?

Explain your debugging methodology, focusing on the steps you take to identify issues in machine learning models. Mention any tools or practices you implement to streamline this process.

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What machine learning frameworks are you most comfortable with?

List the frameworks you have extensive experience in, such as TensorFlow or PyTorch. Discuss specific projects where you leveraged these frameworks to solve complex problems effectively.

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How do you handle multi-tenancy in machine learning systems?

Discuss your understanding of multi-tenancy in ML environments and your experience managing resources efficiently. Emphasize your approach to ensuring isolation and performance across different tenants.

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What tools have you built or used to support automation in machine learning workflows?

Share examples of tools or systems you’ve developed or utilized for automation, explaining how they improved workflow efficiency. Discuss the impact your contributions had on the machine learning lifecycle.

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Why are you interested in working with Flip.shop as a Senior Machine Learning Engineer?

Express your enthusiasm for Flip.shop’s mission and values. Share how your career aspirations align with the company's goals and how your skills can add value to their innovative approach to social commerce.

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Full-time, remote
DATE POSTED
April 8, 2025

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