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ML Engineer

This role is for one of the Weekday's clients

We are seeking a Founding ML Engineer with 3+ years of experience in software development and a strong focus on machine learning, LLMs, and generative AI. This is an exciting opportunity to join an early-stage AI startup, leading cutting-edge AI innovations and playing a key role in shaping ML infrastructure and products.

Key Responsibilities

  • Design, develop, and deploy ML models with a focus on LLMs, generative AI, and model fine-tuning.
  • Build and optimize scalable ML pipelines for efficient data processing and model training.
  • Work with large-scale datasets, enhancing feature engineering and training workflows.
  • Collaborate with cross-functional teams to seamlessly integrate AI solutions into production environments.
  • Stay updated with the latest advancements in AI/ML, researching and implementing innovative techniques.
  • Optimize model inference performance to ensure efficiency in real-world applications.
  • Implement robust monitoring, evaluation, and continuous improvement processes for deployed models.

What We’re Looking For

  • 3+ years of hands-on experience in software development, with a strong focus on machine learning.
  • Proficiency in Python and deep understanding of ML frameworks such as TensorFlow, PyTorch, and Hugging Face.
  • Experience working with LLMs, generative AI, and model fine-tuning is highly preferred.
  • Familiarity with cloud platforms (AWS, GCP, or Azure) and ML infrastructure.
  • Understanding of MLOps best practices, including model versioning, monitoring, and deployment.
  • Strong problem-solving skills and the ability to thrive in a fast-paced startup environment.

Average salary estimate

$110000 / YEARLY (est.)
min
max
$90000K
$130000K

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 ML Engineer, Weekday

Are you ready to embark on an exciting journey as a Founding ML Engineer with one of Weekday's clients? This position is perfect for someone with at least 3 years of experience in software development and a passion for machine learning, especially in the realms of large language models (LLMs) and generative AI. As a key figure in this early-stage AI startup, you’ll have the opportunity to lead cutting-edge innovations that shape ML infrastructure and products. Your responsibilities will include designing, developing, and deploying ML models, focusing on LLMs and model fine-tuning, while building scalable ML pipelines for efficient data processing. Collaborating with cross-functional teams will be essential as you integrate groundbreaking AI solutions into production environments. You’ll also have to stay ahead of the curve by researching the latest advancements in AI/ML and optimizing model performance for real-world applications. If you have a proficiency in Python, a deep understanding of frameworks like TensorFlow and PyTorch, and experience with cloud platforms such as AWS, GCP, or Azure, you’ll thrive in this fast-paced startup environment. Join us and make a significant impact on the world of AI!

Frequently Asked Questions (FAQs) for ML Engineer Role at Weekday
What are the responsibilities of a Founding ML Engineer at Weekday?

As a Founding ML Engineer at Weekday's client, you'll take on several key responsibilities that involve designing, developing, and deploying machine learning models. Your focus will be on large language models (LLMs) and generative AI, where you'll build and optimize scalable ML pipelines for efficient data processing and model training. Collaboration is critical, as you'll work closely with cross-functional teams to ensure smooth integration of AI solutions into production environments. Additionally, you'll stay updated with the latest advancements in AI/ML and implement robust evaluation processes for the deployed models.

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What qualifications do I need for the Founding ML Engineer position at Weekday?

To qualify for the Founding ML Engineer role at Weekday's client, you should possess a minimum of 3 years of hands-on experience in software development with a solid emphasis on machine learning. Proficiency in Python is essential, along with deep knowledge of ML frameworks such as TensorFlow, PyTorch, and Hugging Face. Familiarity with large language models (LLMs), generative AI, and cloud platforms like AWS, GCP, or Azure will greatly enhance your profile. Understanding MLOps best practices, such as model versioning and monitoring, is also crucial.

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What skills are essential for a Founding ML Engineer at Weekday?

The essential skills for a Founding ML Engineer at Weekday's client include proficiency in programming languages like Python, as well as a strong grasp of machine learning frameworks such as TensorFlow and PyTorch. Experience with LLMs and generative AI is highly desirable, alongside familiarity with cloud computing and ML infrastructure. Additionally, you need to demonstrate excellent problem-solving skills and adaptability to thrive in a dynamic startup environment.

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How does the Founding ML Engineer role at Weekday contribute to AI innovations?

In the Founding ML Engineer role at Weekday's client, you play a vital part in driving AI innovations. Your work in developing and deploying advanced machine learning models directly contributes to creating transformative AI solutions. By optimizing ML pipelines and integrating AI into production environments, you ensure that the innovations are scalable and efficient, making a significant impact on both the startup and the industry at large.

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What can I expect in terms of career growth as a Founding ML Engineer at Weekday?

As a Founding ML Engineer at Weekday's client, you can expect significant career growth opportunities due to the nature of working in an early-stage AI startup. You'll have the chance to lead innovative projects and shape the ML infrastructure while collaborating with diverse teams. The exposure to cutting-edge technologies and the freedom to explore new ideas can rapidly boost your career trajectory and expand your skill set in the machine learning field.

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Common Interview Questions for ML Engineer
Can you describe your experience with large language models (LLMs)?

When answering this question, highlight specific projects where you've utilized LLMs, detailing the challenges you faced and the outcomes. Discuss the frameworks you used, like TensorFlow or PyTorch, and how you fine-tuned models to improve their performance within a project.

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What machine learning frameworks are you familiar with, and which do you prefer?

Provide an overview of your experience with various ML frameworks, such as TensorFlow, PyTorch, and others. Explain your preference based on specific project requirements, ease of use, and support for functionalities like LLMs or generative AI, and back it up with examples from your work.

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How do you approach building scalable ML pipelines?

Your response should detail your process for designing ML pipelines. Highlight tools and techniques you use for data collection, preprocessing, model training, and deployment. Discuss how you've tackled challenges like data bottlenecks or deploying in a cloud environment.

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Can you give an example of a successful AI integration project?

For this question, narrate a specific project where you successfully integrated AI solutions. Outline your role, the technology stack used, challenges encountered, and how the integration impacted the business or product positively.

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What techniques do you implement to optimize model inference performance?

Discuss techniques such as model quantization, pruning, or using optimized libraries like TensorRT. Provide an example of a model you worked with, outlining the methods you used for improvement and the results.

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How do you keep up with the latest trends in AI/ML?

Demonstrate your commitment to learning by discussing resources you follow, such as academic papers, industry blogs, or conferences. Highlight specific advancements that have influenced your work and how you apply these insights in real projects.

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What MLOps practices do you incorporate in your work?

Mention practices like model versioning, monitoring, and continuous integration/continuous deployment (CI/CD). Provide a past example where you implemented MLOps and how it ensured model performance and reliability over time.

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Describe a challenging problem you encountered in machine learning and how you solved it.

Here, share a specific problem you faced, the steps you took to address it, and the final outcome. Emphasize your analytical skills and creativity in providing a solution, showcasing how you approached problem-solving in the context of machine learning.

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How do you handle collaboration with non-technical team members?

Describe strategies you use to bridge the gap between technical concepts and non-technical stakeholders. Provide an example that illustrates your ability to communicate complex ideas clearly and effectively while collaborating on projects.

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What are your long-term career goals as a Founding ML Engineer?

Share your aspirations related to the ML field, perhaps emphasizing interests in leading teams, developing innovative AI solutions, or contributing to groundbreaking research. Stress your desire to grow within an organization and the impact you hope to make in the industry.

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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...

54 jobs
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Full-time, remote
DATE POSTED
March 12, 2025

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