Machine Learning Engineer
SweedSalary not specified
Full Time
Mid-level (3 to 4 years)
Not SpecifiedCompensation
Senior (5 to 8 years), Expert & Leadership (9+ years)Experience Level
Full TimeJob Type
UnknownVisa
Artificial Intelligence, TechnologyIndustries
Requirements
- PhD in a technical field or equivalent practical experience
- PhD in Machine Learning, Computer Vision, Natural Language Processing or related areas (advantageous)
- A proven track record of publications and relevant experience in one or more areas such as large foundational models, ML+Systems, optimization, learning theory, computer vision, NLP etc. (advantageous)
- Proven experience with ML frameworks (e.g. JAX) and proven experience with training large models (advantageous)
- Proven experience working in industry, working on projects from proof-of-concept through to implementation, applying experimental ideas to applied problems (advantageous)
- A real passion for AI, Optimization, and Efficiency! (advantageous)
Responsibilities
- Design, implement and evaluate models, agents and software prototypes of large foundational models
- Deep dive into fundamentals of both the ML aspects of foundational models (like architectures, loss functions, data, evals) as well as their implementation on neural accelerators (efficiency during training, serving)
- Report and present research findings and developments including status and results clearly and efficiently both internally and externally, verbally and in writing
- Suggest and engage in team collaborations to meet ambitious research goals
- Work with external collaborators and maintain relationships with relevant research labs and key individuals as appropriate
- Work in collaboration with our Responsible AI teams to ensure our advances in intelligence are developed ethically and provide broad benefits to humanity
Skills
Machine Learning
Optimization Algorithms
Reinforcement Learning
Generative Modeling
Causal Inference
Transformers
Large-scale Optimization
Sampling Techniques
DeepMind
Develops artificial general intelligence systems
About DeepMind
This company leads in the field of artificial general intelligence (AGI), with notable applications across healthcare, energy management, and biotechnology. Their work in early diagnostic tools for eye diseases, optimizing energy usage in major data centers, and groundbreaking contributions to protein structure prediction underlines their commitment to harnessing AI for diverse practical applications. The company's dedication to pushing the boundaries of AI technology not only propels the industry forward but also creates a dynamic and impactful working environment for its employees.
London, United KingdomHeadquarters
2010Year Founded
$4.9MTotal Funding
ACQUISITIONCompany Stage
AI & Machine Learning, BiotechnologyIndustries
1,001-5,000Employees
Benefits
Performance Bonus
Risks
Emerging AI models may challenge DeepMind's current strategies.
Backlash against AI models like Gemini poses reputational risks.
Labeling AI-generated content could increase operational complexity for DeepMind.
Differentiation
DeepMind combines AI, ML, and neuroscience for general-purpose learning algorithms.
DeepMind's AlphaFold model advances protein folding research significantly.
GraphCast by DeepMind offers rapid, accurate ten-day weather forecasts.
Upsides
AI-driven drug discovery is set to grow significantly in 2024.
AlphaCode 2 showcases AI's potential in competitive programming.
DeepMind's AI tools are transforming music creation and meteorology.
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