Head of ML/AI Exploration, Architecture, & Engineering

Key Skills

Aartificial intelligence, LangChain, Machine learning techniques, PyTorch, TensorFlow

Job Description

As the Head of the Applied AI team, your work is to discover, invent, solve, and prototype. From devising experiments and building robust implementations to designing new algorithms, You’ll lead a small team of Research Scientists and work on applying artificial intelligence to critically important, often ambiguous, problems. Our team values individuals who can bridge the gap between innovative research and practical, impactful solutions.

How you will make 10x impact:

• Attract and develop a diverse team of ML/AI experts, as well as guide and coach them on all aspects of their research. Foster a collaborative environment for brainstorming, advising, and knowledge sharing.
• Partner on the technical vision and strategy for our different early stage and early investigation projects; co-design and co-lead a technical roadmap.
• Develop, implement, and deploy robust, scalable ML/AI solutions for real-world problems across multiple X projects and scientific domains, utilizing state of the art developments and techniques with a focus on foundation models and transformer architectures.
• Design and build hybrid AI models, potentially integrating LLMs with other tools and techniques (e.g., graph-based ML, reinforcement learning).
• Provide research and engineering leadership on X early explorations: defining problem scope, identifying optimal AI/ML approaches, and evaluating their merits.
• Guide data strategy and contribute to ML pipeline development and system evaluation.
• Contribute to code reviews, establish best practices for ML engineering, and optimize code for performance and scalability.
• Mentor and guide other team members, act as X’s link to the broader research and academic community, as well as to Alphabet’s other research groups, staying abreast of and integrating the latest advancements.

What you should have:

• PhD in Computer Science, Artificial Intelligence, or a related technical field.
• Experience leading a team of research scientists and in mentoring and guiding junior researchers or engineers.
• Experience in applying ML/AI techniques to complex problems.
• Strong, hands-on experience with LLMs/Transformers, including their theoretical underpinnings and practical application in post-training (e.g., fine-tuning, RLHF, prompting, agent development).
• Experience deploying backend LLM applications.
• Proficiency in Python and deep experience with ML/Deep Learning frameworks (e.g., TensorFlow, PyTorch, JAX, HuggingFace, LangChain).

It’d be great if you also had these:

• Experience with graph-based machine learning techniques.
• Meaningful experience or a strong understanding of applying AI/ML in another scientific discipline such as biology, psychology, neuroscience, or a related field.
• Demonstrable research experience, evidenced by contributions to projects, and ideally through publications in relevant ML/NLP venues (e.g., NeurIPS, ICML, ICLR, ACL, EMNLP).
• Industry experience in a startup or fast-paced R&D environment.

The US base salary range for this full-time position is $248,000 - $345,000 + bonus + equity + benefits. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your location during the hiring process.

Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits.