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GenAI Data Scientist

About Us:

At Articul8 AI, we relentlessly pursue excellence and create exceptional GenAI products that exceed customer expectations. We are a team of dedicated individuals who take pride in our work and strive for greatness in every aspect of our business. We believe in using our advantages to make a positive impact on the world and inspiring others to do the same

Job Description:

Articul8 AI is seeking a Data Scientist to design, develop, and deploy AI-driven solutions that solve real-world problems at scale. You will work on machine learning models, large language models (LLMs), and AI applications while optimizing performance for production environments. This role requires expertise in AI/ML frameworks, cloud platforms, and software engineering best practices.

You will be developing and deploying advanced deep learning and generative AI models and algorithms to enhance existing products or to create new products that fulfill critical business needs. In this role, you will be working closely with Product Management and Engineering teams to build GenAI products at scale. You will be responsible for transforming business needs to technical requirements and for leveraging state of the art research to develop and deliver products. You will also support Engineering with testing and validation of the product.

  • Design, develop, and deploy AI-driven solution in production that solve real-world problems at scale.

  • Train, fine-tune, and optimize deep learning and LLM-based solutions to enhance existing products or to create new products.

  • Evaluate and implement state-of-the-art AI/ML algorithms to improve model accuracy and efficiency to enhance and deliver product.

  • Optimize models ensuring low latency and high availability for cloud and on-prem environments.

  • Collaborate closely with engineering teams and product management to build GenAI products at scale.

  • Work with large-scale datasets, ensuring data quality, preprocessing, and feature engineering.

  • Develop APIs and microservices to serve AI models in production at scale.

  • Handle large-scale datasets, preprocessing, and feature engineering to ensuring data quality.

  • Responsible for transforming business needs to technical requirements to develop and deliver products.

  • Stay up to date with the latest AI trends, research, and best practices.

  • Ensure ethical AI practices, data privacy, and security compliance

Required Qualifications

  • Master’s Degree in Science, Technology, Engineering and Mathematics (STEM) or Statistics with 10 to 15 years of experience

  • In-depth knowledge and experience with algorithms for time series analysis including data pre-processing, pattern recognition, clustering, modeling and anomaly detection.

  • Strong expertise in Deep Learning, Machine Learning and Generative AI models (including Language, Vision, Audio and Multi-modal models)

  • Exposure to one or more of the following domains - Optimization, Stochastic Processes, Estimation theory

  • Experience in deploying deep learning models on multiple GPUs

  • Experience in developing models and algorithms using ML frameworks like PyTorch, TensorFlow

  • Strong programming skills in one or more of the following languages - Python, Golang

  • Experience in building Docker images in creating scalable, efficient, and portable applications

  • Experience in Kubernetes for container orchestration and writing YAML manifests to define how applications and services should be deployed

  • Knowledge of cloud platforms at least one of AWS, Azure, GCP and its services for deployment of applications

  • Strong verbal and written communications skills.

Preferred Qualifications

  • Ph.D, in Science, Technology, Engineering and Mathematics (STEM) or Statistics with 6 to 8 years of experience.

  • Deep expertise and experience in training/fine-tuning large language models on large GPU clusters.

  • Experience in parallel programming including data, model and tensor parallelisms with PyTorch and TensorFlow

  • Deep experience in building and scaling machine learning / deep learning or GenAI applications with Docker and Kubernetes.

  • Strong working experience with at least two cloud service providers (AWS, Azure GCP).

  • Knowledge of CI/CD pipelines, MLOps like MLflow, Kubeflow, or TensorBoard.

  • Deep expertise and experience in one or more of the following areas like finance, healthcare, engineering.

  • Ability to transform business needs to technical requirements, define tasks, metrics and milestones.

  • Ability to communicate technological challenges and achievements to various stakeholders.

What We Offer:

By joining our team, you become part of a community that embraces diversity, inclusiveness, and lifelong learning. We nurture curiosity and creativity, encouraging exploration beyond conventional wisdom. Through mentorship, knowledge exchange, and constructive feedback, we cultivate an environment that supports both personal and professional development.

Your future experience at Articul8 will include continuous learning and growth opportunities as we embark on an exciting journey to disrupt the status quo. If you're excited about joining a team that's passionate about making a difference, we want to hear from you.

In addition to our competitive salary and benefits package, we offer a range of perks and programs designed to help you succeed, including:

  • Professional development opportunities, including training and mentorship programs

  • Flexible work arrangements,

  • Access to the latest technologies and tools

  • Regular social events and team-building activities

  • A supportive and inclusive work environment

If you're ready to join a team that's changing the game, apply now to become a part of the Articul8 team. Join us on this adventure and help shape the future of Generative AI in the enterprise.

Average salary estimate

$140000 / YEARLY (est.)
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$120000K
$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 GenAI Data Scientist, Articul8

At Articul8 AI, we're on the cutting edge of Generative AI technology, and we're looking for a talented GenAI Data Scientist to help us drive innovation and produce top-tier AI solutions. In this role, you'll dive deep into the world of machine learning, developing and deploying advanced models that tackle real-world challenges at scale. If you’re passionate about transforming business needs into tailored technical solutions, you’ll fit right in! Collaborating closely with our engineering and product management teams, you’ll harness the power of large language models and deep learning techniques to enhance existing products or create incredibly impactful new ones. You’ll leverage state-of-the-art AI methods while optimizing for production environments, ensuring low latency and high availability across cloud and on-prem systems. At Articul8 AI, we value diverse perspectives, so you’ll also have the chance to shape ethical AI practices and adhere to data privacy standards. If you have the expertise in AI/ML frameworks, thrive in a collaborative, innovative environment, and are committed to making a difference, this is the role for you. Join us and become a pivotal part of a community that values lifelong learning and creativity as we redefine the future of AI!

Frequently Asked Questions (FAQs) for GenAI Data Scientist Role at Articul8
What are the key responsibilities of a GenAI Data Scientist at Articul8 AI?

As a GenAI Data Scientist at Articul8 AI, your primary responsibilities will include designing, developing, and deploying AI-driven solutions to solve real-world issues. You'll train and optimize deep learning models, work with large-scale datasets, and collaborate with engineering and product teams to deliver powerful GenAI products. Additionally, you'll ensure that the models you create offer high accuracy and efficiency while supporting ethical AI practices.

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What qualifications do I need to apply for the GenAI Data Scientist position at Articul8 AI?

To qualify for the GenAI Data Scientist role at Articul8 AI, candidates should hold a Master’s Degree in a relevant field such as STEM or Statistics with considerable experience in AI/ML frameworks. A strong foundation in deep learning, generative AI models, and expertise in deploying on cloud platforms will set you apart. While 10 to 15 years of experience is preferred, candidates with a Ph.D. and fewer years can also excel, especially in the realm of large language models.

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What technologies will I be working with as a GenAI Data Scientist at Articul8 AI?

In the role of GenAI Data Scientist at Articul8 AI, you will engage with cutting-edge technologies including deep learning frameworks like PyTorch and TensorFlow, as well as cloud services (AWS, Azure, or GCP). You'll also leverage containerization techniques using Docker and Kubernetes, which will enable you to create scalable applications to meet diverse technical requirements.

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How does Articul8 AI support professional development for GenAI Data Scientists?

Articul8 AI places a strong emphasis on continuous learning and development. As a GenAI Data Scientist, you'll have access to mentorship programs, professional training, and the latest tools in the industry. The collaborative environment promotes knowledge exchange, helping you grow your skill set and stay updated with the latest advancements in AI technology.

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Can you describe the work environment for a GenAI Data Scientist at Articul8 AI?

The work environment at Articul8 AI is designed to be supportive, inclusive, and conducive to creativity. As a GenAI Data Scientist, you'll find yourself in a culture that encourages innovation through collaboration and exploration. Regular social events, flexible work arrangements, and a focus on both personal and professional growth make it an exciting place to advance your career.

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Common Interview Questions for GenAI Data Scientist
What is your experience with deep learning models in the role of a GenAI Data Scientist?

When answering this question, share specific examples of projects where you developed or worked with deep learning models. Discuss the techniques you used, the challenges you faced, and how you optimized these models for better performance. Highlight any use of frameworks like PyTorch or TensorFlow and relate it back to real business scenarios.

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How would you approach transforming business needs into technical requirements as a GenAI Data Scientist?

To react effectively to this question, discuss your systematic approach to understanding business needs, collaborating with stakeholders, and breaking down requirements into actionable technical tasks. Use examples from previous experiences where you successfully linked organizational goals with technological deliverables.

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Can you explain how you ensure data quality while working with large-scale datasets?

This is an opportunity to emphasize your experience with data preprocessing, feature engineering, and any automated methods you incorporate to ensure data cleanliness. Discuss tools and techniques you've used in previous projects, underscoring the importance of data quality in machine learning models.

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What steps do you take to stay updated with the latest AI trends and research?

In your response, outline specific actions you take to stay informed, like reading research papers, attending conferences, or participating in online courses. Mention how you apply this new knowledge to your work as a GenAI Data Scientist to drive innovation.

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Describe your experience with deploying machine learning models in production.

You should provide examples of models you've deployed and the processes you followed. Discuss any platforms you've used, such as AWS or Azure, and elaborate on the importance of monitoring, scaling, and maintaining model performance post-deployment.

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How do you handle collaboration with cross-functional teams?

Focus on your communication skills and experiences that highlight collaboration with engineers, product managers, and other stakeholders. Describe how you ensure everyone is on the same page and able to meet project deadlines while achieving mutual goals.

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What are your experiences with ethical AI practices?

Discuss your awareness and knowledge of ethical AI practices, including transparency, fairness, and accountability in algorithm design. Provide examples of how you've implemented ethical considerations into your previous projects as a GenAI Data Scientist.

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How do you optimize models for low latency and high availability?

Explain the techniques you use to ensure models perform efficiently in production, highlighting your understanding of optimization at both the algorithmic level and the infrastructure level. Specific examples of previous work can illustrate the strategies you've successfully implemented.

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What programming languages and tools do you prefer as a GenAI Data Scientist?

Detail your proficiency in programming languages such as Python or Golang, emphasizing your familiarity with their libraries and frameworks relevant to machine learning. Share insights into your favorite tools and why they are effective in your workflow.

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What challenges have you faced in developing AI solutions, and how did you overcome them?

Shed light on specific challenges you faced in previous roles, such as data sparsity or model misbehavior, and explain your problem-solving process. Include how you assessed the situation, the solutions you implemented, and the outcomes of those interventions to reflect your critical thinking and resilience.

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DATE POSTED
March 21, 2025

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