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Senior Machine Learning Scientist

The Company You’ll Join

At Qloo, our cutting-edge Taste AI technology leverages extraordinary amounts of data—over half a billion records of public figures, places, and things, plus a globe-spanning consumer behavior and sentiment database—to unearth deep insights about consumer preferences. From understanding global travel trends to curating the perfect restaurant recommendation based on your unique tastes, our Taste AI engine sifts through the noise to find the signals that matter. 


And the best part? Qloo's API suite is powered by cultural entities, not personal identities, ensuring our insights are derived without relying on personally identifiable information.


Read more about our recent Series C funding here.


The team you’ll work with:

Reporting to the Director of AI, this is a high-impact role where your expertise will directly shape the future of our ML/AI capabilities. Our team values exploration and continuous learning, encouraging you to drive meaningful innovation and take on exciting challenges. If you're a

proactive problem-solver with a passion for machine learning, we'd love to meet you.


Hear what the team has to say  –  “...the fantastic team I work with creates an environment where we encourage each other and collaborate, which naturally leads to creative ideas. The complex technical challenges we face not only keep things interesting but also push us to find unique solutions, and AI constantly inspires me to excel in my role.” - Elizabeth, VP of Applied ML.


The impact you’ll have:

As an ML Scientist at Qloo, you will play a crucial role in developing and implementing cutting-edge machine learning models and data-driven solutions. You will collaborate with cross-functional teams and work on a diverse range of projects, from data exploration and model development to the deployment and monitoring of machine learning systems. 


You'll immediately provide value by:
  • Model Development & Deployment: Develop, test, deploy, and maintain machine learning models and algorithms, ensuring their scalability, robustness, and performance in production. 
  • Data Analysis & Optimization: Conduct data preprocessing, feature engineering, and exploratory analysis to optimize AI/ML models. 
  • Pipeline Development & Enhancement: Design, build, and enhance efficient machine learning pipelines, ensuring their scalability and performance. 
  • Collaboration & Cross-functional Integration: Work closely with software engineers, data engineers, and other teams to integrate ML models into production systems, aligning with business requirements. 
  • Model Performance Monitoring & Improvement: Implement tools for real-time model monitoring, evaluate performance, and drive continuous improvements to models and pipelines. 
  • Experimentation & Innovation: Explore emerging ML techniques, deep learning methods, and advanced algorithms to enhance model capabilities and introduce new solutions. 
  • Knowledge Sharing & Mentorship: Present findings to stakeholders (both technical and non-technical) and contribute to the development of best practices. Mentor junior team members and foster a collaborative team environment. 
  • Continuous Learning: Stay current with industry trends and emerging technologies in data science and machine learning to identify new opportunities and techniques.


To be a successful match you must have:
  • 3+ years in a Machine Learning or ML Engineering role, with hands-on experience in deep learning frameworks (e.g., TensorFlow, PyTorch). 
  • A degree in Mathematics, Engineering, Statistics, Computer Science, Physics, or a related field. An advanced degree is highly preferred. 
  • Proficient in Python and PySpark; experience with SQL or similar querying languages. Solid foundation in machine learning principles, including model evaluation, optimization, and deployment best practices. 
  • Self-motivated, collaborative, and adaptable, with a "can-do" attitude and comfort in a fast-paced, often ambiguous environment. 
  • Excellent communication and interpersonal skills, capable of bridging technical work with business applications. 
  • Experience with model monitoring frameworks and A/B testing. 
  • Familiarity with cloud environments (e.g., AWS, Google Cloud) and deployment of ML models at scale. 
  • Exposure to startup or high-growth company environments.


What we offer:
  • Potential equity package
  • Excellent health insurance coverage, with ability to join group dental and vision for a nominal fee
  • 4% 401K matching
  • 20 paid time off days
  • 5 paid sick days
  • 12 weeks of paid parental leave
  • 10+ annual company holidays 
  • Opportunities for professional development and growth within a dynamic environment
  • A supportive and inclusive company ethos where your ideas are valued, your contributions are recognized, and your impact is tangible
  • The chance to be part of a small but mighty team that's making waves in the industry and shaping the future of technology
  • Beautiful HQ in Soho, NYC with the opportunity to work in-office, if desired


$140,000 - $180,000 a year
Compensation determined based on experience and qualifications. To be discussed during interview process

We are open to different backgrounds and tenure for this hire and compensation will be commensurate with experience. Please note that equity may be included in our total package, depending on role and level.

Average salary estimate

$160000 / YEARLY (est.)
min
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$140000K
$180000K

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 Scientist, Qloo

At Qloo, we're on the cutting-edge of Taste AI technology, and we're looking for a Senior Machine Learning Scientist to join our dynamic team. If you’re ready to dive into over half a billion records of consumer behavior and sentiment, this is the role for you! As a Senior Machine Learning Scientist, you’ll play a pivotal role in shaping our ML/AI capabilities, directly impacting the future of our projects. You'll be involved in everything from developing and deploying robust machine learning models to collaborating with cross-functional teams, ensuring that our solutions not only meet business requirements but exceed them. We've created an environment where exploration, innovation, and teamwork shine, and your contributions will be critical. You'll have the chance to enhance machine learning pipelines, conduct meaningful data analysis, and even mentor junior team members. Plus, we believe in continuous learning, offering opportunities to stay current with the latest industry trends. With a competitive compensation package that includes potential equity, excellent health insurance, and ample paid time off, we provide the support you need to thrive in your career. If you're passionate about machine learning and ready to tackle exciting challenges, come be a part of making waves in the tech world at Qloo!

Frequently Asked Questions (FAQs) for Senior Machine Learning Scientist Role at Qloo
What does a Senior Machine Learning Scientist do at Qloo?

As a Senior Machine Learning Scientist at Qloo, you will develop and implement cutting-edge machine learning models and data-driven solutions. Your role involves collaborating with cross-functional teams, conducting data analysis, optimizing models, and integrating them into production systems, enabling Qloo to uncover deep insights about consumer preferences.

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What qualifications are required for the Senior Machine Learning Scientist position at Qloo?

To qualify for the Senior Machine Learning Scientist role at Qloo, you need at least 3 years of experience in machine learning or ML engineering, proficiency in Python and PySpark, and a strong foundation in deep learning frameworks like TensorFlow or PyTorch. An advanced degree in a related field is highly preferred.

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What kind of projects will a Senior Machine Learning Scientist work on at Qloo?

At Qloo, a Senior Machine Learning Scientist will work on diverse projects ranging from data exploration and model development to the deployment and monitoring of ML systems. You'll explore innovative ML techniques and help enhance our existing models and pipelines.

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What is the work environment like for a Senior Machine Learning Scientist at Qloo?

The work environment at Qloo is collaborative and supportive, encouraging exploration and continuous learning. As a Senior Machine Learning Scientist, you will be part of a team that values innovation and is passionate about tackling complex technical challenges.

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How does Qloo support professional development for its Senior Machine Learning Scientists?

Qloo supports professional development by providing opportunities for continuous learning, mentorship, and growth within a dynamic environment. Senior Machine Learning Scientists are encouraged to present findings, share knowledge, and explore new technologies to enhance their skills.

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What kind of impact can a Senior Machine Learning Scientist make at Qloo?

A Senior Machine Learning Scientist at Qloo will significantly impact the development of our ML capabilities, helping to create innovative solutions that drive consumer insights and enhance our Taste AI technology. Your work will directly influence our ability to deliver tailored recommendations.

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What benefits does Qloo offer to its Senior Machine Learning Scientists?

Qloo offers a comprehensive benefits package for Senior Machine Learning Scientists, which includes potential equity, excellent health insurance, paid time off, 401K matching, and opportunities for professional development. The work-life balance and inclusive environment further enhance your experience at Qloo.

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Common Interview Questions for Senior Machine Learning Scientist
Can you explain a machine learning project you worked on in the past?

When answering this question, describe a specific project and your role in it. Highlight the problem you aimed to solve, the algorithms you chose, and the results achieved. Focus on your contributions and the learnings you gained, making sure to showcase your hands-on experience in machine learning.

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What experience do you have with TensorFlow or PyTorch?

In your answer, detail your experience using either TensorFlow or PyTorch, including any specific projects or tasks where you utilized these frameworks. Discuss your familiarity with their functionalities, and highlight any challenges you faced and overcame while using them.

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How do you approach model evaluation and optimization?

Discuss the techniques you use for model evaluation, such as cross-validation and accuracy metrics. Explain how you analyze model performance and your strategies for optimization, including hyperparameter tuning and feature selection. Provide examples where you successfully applied these methods.

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What strategies do you use for feature engineering?

Describe your experience with feature engineering, including specific techniques you have used to transform raw data into meaningful features. Provide examples of how these engineered features contributed to the success of your machine learning models.

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Can you explain the importance of data preprocessing?

Data preprocessing is crucial for model performance. Explain how you handle missing values, normalization, and data transformation. Discuss any tools or libraries you utilize in the preprocessing stage and illustrate your points with examples from past projects.

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Describe your experience with cloud deployment of machine learning models.

Discuss your familiarity with cloud environments like AWS or Google Cloud, and explain how you've deployed machine learning models at scale in these environments. Detail the processes involved and any tools you used to facilitate deployment and ensure model performance.

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How do you stay current with emerging machine learning trends?

Explain your approach to continuous learning, whether through online courses, attending conferences, or following industry publications. Highlight specific resources you find valuable and how you apply new knowledge to your work as a Senior Machine Learning Scientist.

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How do you handle ambiguity in project requirements?

Discuss your strategies for navigating ambiguous project requirements, emphasizing communication and collaboration with stakeholders. Explain how you clarify goals and utilize iterative processes to refine project objectives and deliver successful outcomes.

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What is your experience with A/B testing?

Describe your understanding of A/B testing within the context of machine learning. Provide examples of how you've conducted A/B tests to validate model performance improvements and how you analyze results to make data-driven decisions.

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How would you explain complex machine learning concepts to a non-technical audience?

Emphasize your communication skills and your ability to translate technical jargon into relatable terms. Offer strategies for simplifying complex concepts, such as using analogies or visual aids. An example from your past where you successfully communicated a technical idea can reinforce your answer.

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Qloo is the leading cultural AI platform, leveraging deep intelligence to connect and predict consumer taste across domains including music, film, consumer products, fashion, hospitality and travel. Qloo's artificial intelligence platform has been...

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Full-time, remote
DATE POSTED
November 27, 2024

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