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Machine Learning Engineer - Ai

At Wasabi, we’re a proven collection of pioneers, visionaries and disruptive doers. We see things differently than our competitors, and we make our mark in the industry by challenging the norm and delivering the unexpected and improbable. We’re a fast-growing company taking the Cloud Storage industry by storm and recognized as one of the best places to work in Boston. 

 

Wasabi hot cloud storage is a new class and category of cloud storage, breaking all traditional barriers and boundaries of storage with a disruptive value proposition of being 1/5th the cost of AWS S3, faster than the competition, with no fees for egress or API request and delivered as a single-tier solution. Cloud storage has never been so simple, so fast and so inexpensive. It’s all part of our vision to make cloud storage the next great global utility, just like electricity.


Role Description: Senior Machine Learning Engineer

 

Role Purpose: 


Wasabi is seeking an experienced Senior Software Engineer with a solid background in machine learning and software development to contribute to Wasabi AiR. In the spirit of our disruptive approach to cloud storage our AI/ML product, Wasabi AiR resets the paradigm of how cloud storage and machine-learning compliment each other and enrich the accessibility of data. This role is perfect for candidates who thrive in team-oriented environments, enjoy mentoring, lead complex projects, and are passionate about building scalable, high-quality machine learning solutions.  


*Principals only. No recruiters.


Responsibilities:
  • Drive advancements in AI, keeping up-to-date with the latest research and applying innovative techniques in production. 
  • Develop and refine computer vision algorithms for tasks such as object detection, tracking, and scene understanding
  • Design & implement NLP/LLM model fine-tuning, deployment, & integrations
  • Apply machine learning technologies to enable systems to learn and adapt to complex situations. 
  • Collaborate closely with cross-functional teams to ensure smooth integration of machine learning capabilities across projects. 
  • Perform testing, debugging, and documentation of machine learning models to ensure reliable installation and maintenance. 


Requirements:
  • 3+ years in architecting, designing, developing, integrating, and supporting complex AI systems.
  • Proficiency in one or more object-oriented programming languages, such as Python, Java, or Golang, with experience in distributed systems. 
  • Deep understanding of large-scale data processing systems and computing frameworks, with a proven ability to optimize and troubleshoot machine learning models. 
  • Hands-on experience ML training and fine-tuning large models with in-house data. 
  • Strong communication and problem-solving abilities, with the ability to document and adhere to timelines effectively. 
  • Master’s Degree or PhD in Computer Science, Data Science, or a related field preferred. 


Wasabi Technologies is an Equal Opportunity Employer. We prohibit discrimination and harassment of any kind based on race, color, sex, religion, sexual orientation, national origin, disability, genetic information, pregnancy, or any other protected characteristic as outlined by federal, state, or local laws.

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CEO of Wasabi Technologies
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What You Should Know About Machine Learning Engineer - Ai, Wasabi Technologies

At Wasabi, a leading innovator in the cloud storage industry, we are on the lookout for a talented Machine Learning Engineer to join our vibrant remote team in the United States. Our mission is to redefine the cloud storage landscape with our disruptive services that are not only cost-efficient but also simplify the storage process for everyone. As a Senior Machine Learning Engineer, you will contribute significantly to our cutting-edge product, Wasabi AiR. This role is tailor-made for those passionate about AI, eager to tackle complex projects, and excited to be part of a team that challenges the norm. Your daily tasks will consist of developing advanced computer vision algorithms, fine-tuning NLP/LLM models, and applying machine learning technologies that revolutionize the way our systems learn and adapt. You'll have the opportunity to collaborate with cross-functional teams, ensuring that our machine learning capabilities are seamlessly integrated across various projects. With 3+ years of experience in architecting and supporting complex AI systems, along with proficiency in programming languages such as Python or Java, you’ll excel in this role. Your strong communication skills will enable you to mentor others while your problem-solving abilities will keep you ahead of the curve in the fast-paced world of technology. Join Wasabi and help us make cloud storage the next great global utility!

Frequently Asked Questions (FAQs) for Machine Learning Engineer - Ai Role at Wasabi Technologies
What are the responsibilities of a Machine Learning Engineer at Wasabi?

A Machine Learning Engineer at Wasabi is tasked with driving advancements in AI by applying the latest research to practical production models. You'll develop and refine algorithms for computer vision tasks, fine-tune NLP models, and collaborate with cross-functional teams to ensure the seamless integration of machine learning capabilities across various projects.

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What qualifications do you need for the Machine Learning Engineer position at Wasabi?

To qualify for the Machine Learning Engineer position at Wasabi, candidates should have 3+ years of experience in developing and supporting AI systems. Proficiency in languages like Python or Java is essential, along with a deep understanding of large-scale data processing systems. A Master’s Degree or PhD in a related field is preferred, showcasing your advanced knowledge in computer science or data science.

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What programming languages are preferred for the Machine Learning Engineer role at Wasabi?

For the Machine Learning Engineer role at Wasabi, candidates should be proficient in one or more object-oriented programming languages, primarily Python, Java, or Golang. Your expertise in these languages will play a pivotal role in creating and optimizing machine learning models.

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How does Wasabi’s approach to cloud storage differ from its competitors for Machine Learning Engineers?

Wasabi’s approach to cloud storage is revolutionary, offering a single-tier solution at a fraction of the cost compared to competitors like AWS S3. This unique positioning allows Machine Learning Engineers to develop scalable and high-quality ML solutions that are both fast and cost-effective, truly transforming the cloud storage experience.

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What is the work culture like for Machine Learning Engineers at Wasabi?

The work culture for Machine Learning Engineers at Wasabi is collaborative and inclusive, emphasizing teamwork and innovation. You'll find yourself in a dynamic environment where mentoring and sharing knowledge are encouraged, allowing you to grow alongside passionate professionals in the field.

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Common Interview Questions for Machine Learning Engineer - Ai
Can you describe a machine learning project you worked on and your role in it?

In responding to this question, focus on a specific project where you played a key role. Highlight the challenges you faced, the machine learning techniques you employed, and the impact your contributions had on the project’s success, demonstrating your practical experience as a Machine Learning Engineer.

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How do you stay up to date with the latest developments in AI and machine learning?

Showcase your commitment to continuous learning by discussing various resources you use, such as research papers, online courses, or AI conferences. This reflects your passion for the field and your proactive approach to implementing the latest technologies in your work as a Machine Learning Engineer.

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What experience do you have with designing and implementing computer vision algorithms?

Discuss specific examples of computer vision algorithms you have designed and implemented, detailing the technologies you used, the challenges you faced, and how your work made a difference in the project. Providing metrics or results will make your answer stand out.

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How do you handle performance bottlenecks in machine learning models?

Address this question by mentioning your systematic approach to identifying performance bottlenecks, using techniques like profiling and algorithm optimization. Provide examples of past experiences where you successfully overcame these challenges, demonstrating your skills and problem-solving abilities.

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What techniques do you use for model fine-tuning?

In your response, describe the specific techniques you employ for fine-tuning models, such as hyperparameter tuning, transfer learning, or data augmentation. Share any tools or libraries you’re familiar with (like TensorFlow or PyTorch) that assist you in this process, emphasizing your technical skills as a Machine Learning Engineer.

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Have you worked with distributed systems? If so, can you describe your experience?

Discuss your experience with distributed systems, focusing on the frameworks you’ve utilized (like Hadoop or Spark) and the context in which you employed them. Highlight the benefits you observed while working with these systems, particularly concerning machine learning model training and deployment.

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How do you ensure the reliability of machine learning models?

Explain your approach to ensuring model reliability, including testing, validation techniques, and performance monitoring. Use specific examples to illustrate how you have successfully guaranteed the stability and reliability of machine learning models in past projects.

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What challenges have you faced in implementing machine learning solutions, and how did you overcome them?

Share particular challenges you have encountered in previous projects, such as data quality issues or integration hurdles. Discuss how you navigated these obstacles, showcasing your problem-solving skills and resilience as a Machine Learning Engineer.

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Can you explain your experience with natural language processing?

Provide an overview of your experience with NLP, detailing projects you have worked on involving language models or text analysis. Highlight specific techniques or libraries that you used and their outcomes, demonstrating your expertise in the field.

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What do you see as the future of AI in cloud storage?

Share your vision for the future intersection of AI and cloud storage, touching on potential innovations and enhancements in storage efficiency and accessibility. This question allows you to showcase your forward-thinking mindset and alignment with Wasabi’s disruptive approach.

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For more than a decade, cloud storage has been controlled by three industry giants who locked users into their expensive proprietary systems. Then came Wasabi and a different idea: cloud storage would become a commodity. Our architecture delivers ...

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Full-time, remote
DATE POSTED
January 5, 2025

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