Research Engineering Technical Lead, AlphaEarth, DeepMind
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Minimum qualifications:
- Bachelor’s degree in Computer Science, Mathematics, Applied Stats, Machine Learning, or equivalent practical experience.
- 8 years of experience in software development.
- Experience in Python or C++, algorithm design, and machine learning.
- Experience acting as a Technical Lead, guiding system architecture and milestone delivery.
Preferred qualifications:
- Experience with large-scale data pipelines, distributed systems, and ML frameworks (e.g. JAX).
- Experience working on deployed projects from proof-of-concept through to implementation.
- Experience driving execution across a 5-10 person engineering/research team. Ability to balance unknowns and ambiguity with forward progress.
- Expertise in earth observation, remote sensing, or related fields.
- Demonstrated engineering excellence and execution efficiency.
About the job
Artificial intelligence will be one of humanity’s most transformative inventions. At DeepMind, we are a pioneering AI lab with exceptional interdisciplinary teams focused on advancing AI development to solve complex global challenges and accelerate high-quality product innovation for billions of users. We use our technologies for widespread public benefit and scientific discovery, ensuring safety and ethics are always our highest priority.
US: $207000 - $300000 (USD) + 20% bonus target + equity + benefits
Learn more about benefits at Google.
Responsibilities
- Act as a Technical Lead for 2-4 engineers, owning technical workstreams end-to-end, planning milestones, and driving execution from proof-of-concept prototypes to production systems.
- Architect, build, and scale large-scale data pipelines, distributed training infrastructure, and low-cost, interactive-speed model inference systems.
- Run experiments and test hypotheses with researchers and engineers to evaluate modeling and systems improvements across the machine learning life cycle.
- Collaborate with team members across London and New York, adapting as project priorities shift across phases of development.
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