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Backend Engineer

This role is for one of the Weekday's clients

We are looking for a Machine Learning Engineer to design, deploy, and optimize LLMs and multi-agent AI systems for healthcare automation. If you are passionate about AI in healthcare, have expertise in Python, Kubernetes, GCP, and ML frameworks, and enjoy working in a fast-paced, research-driven environment, this role is for you!

Key Responsibilities:

  • Develop and optimize LLMs and multi-agent AI systems for healthcare automation.
  • Build Python-based microservices using FastAPI (preferred) for seamless integration and scalability.
  • Deploy, orchestrate, and manage ML services on Kubernetes & GCP to ensure high availability and performance.
  • Utilize ML frameworks like TensorFlow and PyTorch to develop cutting-edge AI solutions.
  • Conduct research and AI advancements to improve model efficiency, accuracy, and adaptability.
  • Collaborate with cross-functional teams to integrate AI-powered solutions into real-world healthcare applications.

What We’re Looking For:

  • Proficiency in Python, with FastAPI experience being a plus.
  • Strong machine learning expertise, including hands-on experience with LLMs, TensorFlow, PyTorch, and multi-agent AI systems.
  • Experience deploying ML models in Kubernetes & GCP for scalable AI solutions.
  • Ability to optimize ML models for efficient performance in production environments.
  • Passion for AI-driven healthcare innovation and a research-driven mindset.
What You Should Know About Backend Engineer, Weekday

Are you ready to step into an exciting opportunity as a Backend Engineer with one of the Weekday's clients? We're on the lookout for a skilled professional who is passionate about using AI to revolutionize healthcare. In this role, you'll have the chance to design, deploy, and optimize sophisticated large language models (LLMs) and multi-agent AI systems that aim to improve healthcare automation. If you have a strong command of Python, a knack for Kubernetes, and experience with Google Cloud Platform (GCP) and various ML frameworks, this is the perfect opportunity for you to thrive in a fast-paced, research-oriented environment. As a Backend Engineer, your responsibilities will include building Python-based microservices, preferably with FastAPI, ensuring seamless integration of applications within scalable infrastructures. You'll be deploying and managing machine learning services on Kubernetes and GCP, ensuring high availability and performance. Moreover, you'll dive into research and advancements in AI to enhance model efficiency, accuracy, and adaptability. Collaborating with cross-functional teams, you'll bring innovative AI solutions into real-world healthcare applications. If you’re ready to make a significant impact in AI-driven healthcare innovation, we want to hear from you!

Frequently Asked Questions (FAQs) for Backend Engineer Role at Weekday
What are the primary responsibilities of a Backend Engineer at Weekday's client?

As a Backend Engineer, you'll primarily focus on developing and optimizing large language models and multi-agent AI systems to facilitate healthcare automation. This includes building Python-based microservices, deploying and managing ML services on Kubernetes and GCP, and utilizing frameworks like TensorFlow and PyTorch to create cutting-edge AI solutions.

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What qualifications are necessary for a Backend Engineer position with Weekday's client?

To qualify for the Backend Engineer role with Weekday's client, candidates should possess proficiency in Python, with FastAPI experience being a plus. Strong expertise in machine learning, familiarity with LLMs, and hands-on experience with TensorFlow and PyTorch are essential. Additionally, experience deploying ML models using Kubernetes and GCP is crucial for this role.

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How does a Backend Engineer at Weekday's client contribute to healthcare innovation?

A Backend Engineer at Weekday's client contributes to healthcare innovation by developing and optimizing AI solutions that automate healthcare processes. This involves conducting research to enhance model efficiency, collaborating with cross-functional teams, and integrating AI-powered solutions into real-world applications, ultimately improving patient outcomes and operational efficiency.

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What is the work environment like for a Backend Engineer at Weekday's client?

The work environment for a Backend Engineer at Weekday's client is fast-paced and research-driven. Employees can expect an atmosphere that encourages innovation and creative problem-solving, collaboration with talented professionals, and a commitment to improving healthcare through advanced technology.

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What programming languages are important for a Backend Engineer at Weekday's client?

For a Backend Engineer role at Weekday's client, proficiency in Python is crucial. Familiarity with FastAPI is advantageous, and experience with machine learning frameworks like TensorFlow and PyTorch will also be beneficial for the tasks involved in the role.

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Common Interview Questions for Backend Engineer
Can you explain how you've utilized Python in your previous backend engineering projects?

In previous projects, I utilized Python to develop robust applications, focusing on scalable microservices. I employed frameworks such as FastAPI to enhance performance and optimize efficiency, showcasing my ability to build high-quality back-end systems.

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What experience do you have with deploying machine learning models in a Kubernetes environment?

I have significant experience deploying machine learning models in Kubernetes. This involved setting up the necessary infrastructure, configuring pods, and utilizing Kubernetes services for monitoring and scaling applications effectively.

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How do you ensure high performance and availability in ML services?

To ensure high performance and availability, I focus on optimizing ML models for production environments, using techniques like model pruning and quantization. Additionally, I implement load balancing and autoscaling capabilities within Kubernetes to manage traffic effectively.

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Can you describe your experience with GCP and its relevance to backend engineering?

I have hands-on experience with Google Cloud Platform, including deploying applications using Cloud Run and leveraging BigQuery for data analysis. This experience has allowed me to effectively manage cloud resources and integrate ML solutions into scalable back-end architectures.

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What machine learning frameworks are you most familiar with?

I'm most familiar with TensorFlow and PyTorch, which I have used extensively to develop and fine-tune machine learning models. I appreciate their flexibility and the ease with which I can implement complex algorithms for AI solutions.

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How do you keep yourself updated with the latest advancements in machine learning?

I stay updated with advancements in machine learning by attending workshops, participating in online courses, and following influential researchers in the field. Engaging in community forums and contributing to open-source projects also helps me stay abreast of emerging trends.

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What steps do you take when optimizing ML models for production?

When optimizing ML models for production, I focus on reducing complexity, improving inference speed, and ensuring robustness. Techniques like hyperparameter tuning, feature selection, and using efficient data formats play a crucial role in this process.

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What do you consider the biggest challenges when integrating AI into healthcare applications?

The biggest challenges when integrating AI into healthcare applications include addressing data privacy concerns, ensuring model interpretability, and overcoming resistance to change from healthcare professionals. Collaborating closely with stakeholders to understand their needs is vital to mitigate these challenges.

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Can you share an experience where you successfully collaborated with a cross-functional team?

I successfully collaborated with a cross-functional team on a project that required integrating AI solutions into a clinical decision support system. By actively communicating with data scientists, UX designers, and healthcare professionals, we were able to deliver a comprehensive product that met everyone’s expectations.

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Why are you interested in the Backend Engineer position at Weekday's client?

I'm interested in the Backend Engineer position at Weekday's client because it aligns with my passion for AI in healthcare. The opportunity to work on innovative solutions that can truly make a difference excites me, and I believe my skills in Python and machine learning can contribute to the team's success.

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Founded in 2002, Weekday currently ships to 97 online markets and has stores in 14 countries, offering a unique retail experience and a carefully curated mix of external brands, limited edition collaborations and a carefully curated selection of s...

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Full-time, remote
DATE POSTED
March 13, 2025

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