T e c h n i c a l L e a d , E a r l y S t a g e S u p p l y C h a i n P r o j e c tSoftware Engineering Mountain View, CA (HQ)
About the Team: We're X's moonshot for the global supply chain, applying AI to reduce waste, fragility, and inefficiency. We're an agile team of experienced AI researchers, software engineers, and entrepreneurs working with visionary partners and customers around the world to ensure sustainable and reliable access to essential goods. You'll be part of a fast-paced team that has the agility and impact of an early-stage company, while building on world-class Google AI technology.
About the Role: You will play a pivotal role as a hands-on technical leader, entrusted with the ownership and responsibility for the technical direction and implementation of critical AI systems. This role requires a deep passion for problem-solving and experimentation, moving across the full range of applied machine learning and software engineering tasks from initial prototyping to building full-scale, robust solutions. You will contribute individually to high-impact technical work while also providing technical guidance and mentorship to other engineers. You will serve as a critical bridge between cutting-edge AI research and real-world enterprise applications within the global supply chain domain. This is an incredibly dynamic role requiring strong cross-functional communication, organization, and planning in a loosely structured, fast-paced environment.
How you will have 10X impact: - Set the technical direction for both research prototypes and production deliverables, driving key decisions on software architecture and features.
- Develop and deliver high-quality, production-grade AI enterprise software from ideation and architectural design to development, testing, deployment, and ongoing maintenance in complex enterprise environments.
- Build the whole solution, encompassing data acquisition, data processing pipelines, and ML modeling.
- Enhance AI reasoning by innovating on how Foundation Models are utilized, improving internal workflows, and developing/integrating specialized tools.
- Actively explore, apply, and innovate state-of-the-art LLM and machine learning techniques.
- Lead and mentor technical initiatives, guiding project execution and cultivating a strong technical capability within the team.
- Ensure responsible AI development, implementing robust safety principles, including sandboxing and traceability of self-modifications, to mitigate risks and ensure alignment with business objectives and ethical guidelines.
- Develop experiences that inspire confidence, delight, and resonate with end users, encouraging adoption and trust.
- Be an active engineer who is willing to "get your hands dirty" in the implementation of solutions.
- Balance longevity with rapid execution, working to bring prototypes to productization.
What you should have: - MS/PhD degree or equivalent practical experience in computer science, engineering, or a related scientific or quantitative field.
- 10+ years experience conducting applied ML research and high-performance implementations of machine learning algorithms, translating research concepts into robust, production-ready systems.
- 7+ years experience designing, developing, maintaining, and releasing production-grade enterprise/business software.
- 4+ years experience as a technical lead for a small team, or equivalent technical leadership experience.
- Extensive applied research experience with:
- Applying LLMs and agentic AI, particularly with techniques like RAG or knowledge graphs.
- Achieving strong results with sophisticated model prompting.
- MLOps, including model deployment, versioning, and performance monitoring in production environments.
- Innovating ways to improve model accuracy and quantify drift, overfitting, and regression.
- Deep learning frameworks like PyTorch, Tensorflow, JAX.
- Optimizing system/model performance (e.g., speed, cost, throughput).
- Python development, with experience in the latest Python toolchains and frameworks, including developing for various platforms (e.g., full-stack web applications, backend services, data pipelines).
- Extensive enterprise software experience with:
- Using LLMs to optimize software development processes and workflows.
- Collaborative software development workflows and platforms including GitHub, agile development/scrum, unit testing, CI/CD, and production operations.
- Integrating AI into enterprise software environments, including Large Language Models (LLMs), Foundation Models, multi-agent system architectures and their orchestration agentic behaviors, tool use, and reasoning capabilities.
- Integrating software with complex enterprise legacy systems, including ERP integration (e.g., SAP, Oracle).
- Deploying and managing applications on major cloud platforms (e.g., Google Cloud Platform, AWS, Azure) and an understanding of underlying infrastructure primitives (e.g., Kubernetes, Terraform).
- Experience working in a startup or equivalent fast-paced environment, able to thrive and execute quickly in an environment of change and uncertainty.
- Excellent written and verbal communication skills, adept at explaining complex technical concepts to both technical and non-technical audiences in a clear and concise manner.
- Excellent organization and planning skills.
- Ability to go deep into technical problems and work closely with engineers and technical leads, coupled with the ability to see the big picture of technical tradeoffs and direction.
It'd be great if you also had these: - Experience with supply chain-related enterprise software applications for procurement, sourcing, product lifecycle management, or supply chain management.
- Experience with Google's AI tools and platforms.
- Experience with Google Cloud and Workspace.
- Research papers or other public-facing documents or presentations that demonstrate technical thought leadership and clarity.
- Experience with data pipelines and storage (e.g., GCS, S3, DataFlow, BigQuery).
The US base salary range for this full-time position is $262,000 - $369,000 + 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.
