Senior Data Scientist - Large Language Models / Generative AI

Posted 19 Hours Ago
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New York, NY
Hybrid
187K-240K Annually
5-7 Years Experience
Artificial Intelligence • Cloud • Software • Cybersecurity
We are building the monitoring and security platform for developers, IT ops teams and business users in the cloud age.
The Role
Contribute to building features using large language models and generative AI technologies. Collaborate with engineers and data scientists to improve and implement state-of-the-art models and agents. Work on projects such as fine-tuning infrastructure, deploying models for real-time use cases, and supporting AI research and development.
Summary Generated by Built In

<strong>Senior Data Scientist - Large Language Models / Generative AI</strong><br>Our Data Science Large Language Models team uses advanced generative AI technologies to create powerful features within the Datadog application. Our focus lies in the fine-tuning, training, and serving of LLMs to power features across the Datadog platform. As a data scientist on the team, you will contribute to building the foundation of impactful features using LLMs as a core computation unit to enable our users to understand their data and systems, reason, plan, and act. You will get the opportunity to collaborate with a group of skilled engineers and data scientists to improve and implement state-of-the-art Large Language Models and Agents to have a direct impact on Datadog products (see Bits AI, your new DevOps copilot for example)<br>At Datadog, we place value in our office culture - the relationships that it builds, the creativity it brings to the table, and the collaboration of being together. We operate as a hybrid workplace to ensure our employees can create a work-life harmony that best fits them.<br><strong>What You'll Do: </strong><br><ul> <li>Work on a wide range of projects, building large-scale distributed fine tuning and training infrastructure, deploying LLMs on GPU instances for real-time use cases, designing robust, secure infrastructure, or supporting cutting-edge AI research and development. </li> <li>Create new product features using advanced machine learning algorithms, LLMs, and statistical techniques</li> <li>Collaborate with a group of AI specialists and scientists in envisioning the future state of our abilities while also aiding in the design and deployment of crucial services.</li> <li>Actively participate in our journal club by reading and presenting latest research papers in the field of LLMs and Generative AI </li> <li>Provide deeper insights and stories behind massive data processed in Datadog systems</li> <li>Develop, deploy, monitor and maintain the LLM models, services, and infrastructure managed by your team and participate in your team's on-call rotation</li> </ul> <br><strong>Who You Are: </strong><br><ul> <li>You possess a BS/MS/PhD in Computer Science, Engineering, Machine Learning or a related scientific field or have equivalent experience</li> <li>You have relevant experience with Language Models (Large LMs is a plus), NLP, large-scale systems and data sets, deep learning, or adjacent fields. Writing production data pipelines and applications is a plus.</li> <li>You have experience with the stack for distributed training and inference of large models including distributed training and inference frameworks, and ML development frameworks such as Pytorch, Tensorflow, etc. Experience with CUDA is a plus.</li> <li>You possess the ability to elaborate complex models and ideas to non-technical personnel</li> <li>You value code simplicity and performance</li> <li>You are passionate about Generative AI and want to contribute to user-facing product</li> </ul> <br>Datadog values people from all walks of life. We understand not everyone will meet all the above qualifications on day one. That's okay. If you're passionate about technology and want to grow your skills, we encourage you to apply. <br><strong>Benefits and Growth: </strong><br><ul> <li>Competitive global benefits </li> <li>New hire stock equity (RSUs) and employee stock purchase plan (ESPP)</li> <li>Opportunity to collaborate closely with colleagues across the Datadog offices in New York City and Paris</li> <li>Opportunity to attend and present at conferences and meetups</li> <li>Intra-departmental mentor and buddy program for in-house networking</li> <li>An inclusive company culture, ability to join our Community Guilds (Datadog employee resource groups)</li> </ul> <br>Benefits and Growth listed above may vary based on the country of your employment and the nature of your employment with Datadog.<br>#LI-TB1<br>Datadog offers a competitive salary and equity package, and may include variable compensation. Actual compensation is based on factors such as the candidate's skills, qualifications, and experience. In addition, Datadog offers a wide range of best in class, comprehensive and inclusive employee benefits for this role including healthcare, dental, parental planning, and mental health benefits, a 401(k) plan and match, paid time off, fitness reimbursements, and a discounted employee stock purchase plan.<br>The reasonably estimated yearly salary for this role at Datadog is:<br>$187,000 - $240,000 USD <br><strong>About Datadog: </strong><br>Datadog (NASDAQ: DDOG) is a global SaaS business, delivering a rare combination of growth and profitability. We are on a mission to break down silos and solve complexity in the cloud age by enabling digital transformation, cloud migration, and infrastructure monitoring of our customers' entire technology stacks. Built by engineers, for engineers, Datadog is used by organizations of all sizes across a wide range of industries. Together, we champion professional development, diversity of thought, innovation, and work excellence to empower continuous growth. Join the pack and become part of a collaborative, pragmatic, and thoughtful people-first community where we solve tough problems, take smart risks, and celebrate one another. Learn more about #DatadogLife on Instagram , LinkedIn, and Datadog Learning Center. <br><strong>Equal Opportunity at Datadog:</strong><br>Datadog is an Affirmative Action and Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. Here are our Candidate Legal Notices for your reference.<br><strong>Your Privacy:</strong><br>Any information you submit to Datadog as part of your application will be processed in accordance with Datadog's Applicant and Candidate Privacy Notice .

Top Skills

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TensorFlow

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The Company
HQ: New York, NY
5,000 Employees
Hybrid Workplace
Year Founded: 2010

What We Do

Datadog (NASDAQ: DDOG) is a global SaaS business, delivering a rare combination of growth and profitability. We are on a mission to break down silos and solve complexity in the cloud age by enabling digital transformation, cloud migration, and infrastructure monitoring of our customers' entire technology stacks. Built by engineers, for engineers, Datadog is used by organizations of all sizes across a wide range of industries. Together, we champion professional development, diversity of thought, innovation, and work excellence to empower continuous growth. Join the pack and become part of a collaborative, pragmatic, and thoughtful people-first community where we solve tough problems, take smart risks, and celebrate one another.

Why Work With Us

At Datadog, we learn from and celebrate each other daily - each win is a team win. Datadogs solve tough problems, innovate pragmatically, and grow together. We promote from within, provide mentorship and opportunities for career development, and support our colleagues in the process. Best of all? We truly love what we do.

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Datadog Offices

Hybrid Workspace

Employees engage in a combination of remote and on-site work.

We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them and their team.

Typical time on-site: 3 days a week
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