Manager I, Engineering - Machine Learning Observability
- Customer centric innovation : Always prioritize the needs and feedback of our customers. Our solutions must simplify their challenges and enhance their machine learning journey.
- User experience matters : A powerful tool is only as good as its usability. Always strive for intuitive, user-friendly designs that enhance customer engagement.
- Collaborative excellence : Every voice matters. Leverage the diverse expertise within our team - software engineering, UX design, product management, applied science - to create well-rounded and effective solutions.
- End-to-End ownership : Take responsibility for our creations from ideation to deployment and maintenance. Pride in our work translates to higher quality products.
- Efficient execution : Balance innovation with practicality. Prioritize tasks and features that align closely with our mission and offer the most value to our customers.
- Agility in action : While planning is essential, the ability to adapt and iterate based on real-world feedback is paramount. Embrace change as an opportunity for improvement.
- Transparent communication : Promote open dialogue about challenges, successes, and decisions. Honesty fosters trust and accelerates problem-solving.
- Scientific rigor : Ensure that our solutions are backed by solid research and empirical evidence. Prioritize robustness and accuracy in our observability tools.
- Continuous learning : Stay updated with the latest advancements in observability for machine learning. Embrace opportunities for professional growth and encourage knowledge-sharing.
- Ethical responsibility : Commit to ensuring that our tools promote fairness, transparency, and accountability in AI. Drive ethical considerations in all that we build.
- LLM Observability announcement blog
- Another blog about chaining
- DASH keynotes
- Product documentation
- Hallucination detection
- Manage and mentor a team of 3-5 engineers, fostering a collaborative and innovative work environment
- Leverage your technical expertise in software engineering to guide the team in building robust and scalable solutions
- Apply your experience with LLMs to enhance the product's capabilities in evaluating and monitoring LLM-based applications
- Explore and implement new techniques and tools to provide deeper insights into model behavior, drift, fairness, and interpretability
- Engage with senior management and executives, articulating complex technical concepts clearly and precisely
- Stay current with industry trends and advancements in machine learning and observability, driving innovation within the team
- Proven experience in software engineering, with a focus on engineering LLM-based systems
- Demonstrated experience managing small teams of software engineers and/or applied scientists, with a track record of delivering high-quality products
- Strong software development skills and proficiency in Python and Go
- Excellent communication abilities to convey complex technical concepts clearly
- A collaborative mindset and proven experience in working in cross-functional teams
- A proactive approach with a passion for continuous learning and innovation
- Experience in applied science, strong understanding of machine learning theory, statistics, and fundamentals is a bonus
- New hire stock equity (RSUs) and employee stock purchase plan (ESPP)
- Continuous professional development, product training, and career pathing
- Intradepartmental mentor and buddy program for in-house networking
- An inclusive company culture, ability to join our Community Guilds (Datadog employee resource groups)
- Access to Inclusion Talks, our Internal panel discussions
- Free, global Spring Health benefits for employees and dependents age 6+
- Competitive global benefits
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