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Machine Learning Scientist

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RWE

26d ago

  • Job
    Full-time
    Mid Level
  • Data
  • Seattle

AI generated summary

  • You must have a Ph.D. or Master’s in a relevant field, 3+ years of industry experience, a strong background in machine learning, mathematical proficiency, programming skills, cloud computing knowledge, and a passion for innovation. Expertise in AI methods and strong communication skills are essential.
  • You will design and implement cutting-edge neural network architectures, collaborate with experts, integrate models into pipelines, stay updated on advancements, develop reusable components, and contribute to research in the machine learning community.

Requirements

  • Ph.D. or Master’s degree in Computer Science, Electrical Engineering, Mathematics, Statistics, or a related field and 3+ years of relevant industry experience
  • Proven track record of research and publications in machine learning, particularly in the areas of diffusion models, generative models, NLP, or related topics.
  • Solid understanding of neural network fundamentals, including convolutional neural networks (CNNs), recurrent neural networks (RNNs), and attention mechanisms.
  • Strong mathematical background, including proficiency in linear algebra, probability theory, and optimization.
  • Proficiency in programming languages such as Python and Julia, and experience with developing large scale models using machine learning packages (e.g., PyTorch, TensorFlow, Jax).
  • Experience with cloud computing platforms such as AWS, Azure, or Google Cloud Platform
  • Experience with deploying machine learning models in production using containerization and orchestration tools (e.g., Docker, Kubernetes)
  • Familiarity with version control systems (e.g., Git), continuous integration/continuous deployment (CI/CD) pipelines, and infrastructure-as-code tools
  • A passion for innovation and staying abreast of the latest research in AI methods relevant to our work in the Lab
  • Strong communication and collaboration skills, with the ability to work effectively in cross-functional teams and contribute to a positive team climate
  • Advantageous, but not a must:
  • Domain expertise in meteorology, climate science or the energy sector
  • Experience with distributed systems, parallel computing, and GPU acceleration is a plus.
  • Proficiency in database technologies for data storage and retrieval (e.g., PostgreSQL, MongoDB, BigQuery)
  • Proficiency in Nvidia GPU frameworks (CUDA, cuDNN, TensorRT, NCCL) and HPC technologies
  • Experience with Google Cloud Platform MLOps tools (e.g., Vertex AI)
  • Publication record in AI conferences (e.g., NeurIPS, ICML) and journals

Responsibilities

  • Experiment, design, develop, and implement novel neural network architectures to build state-of-the-art diffusion models and generative models
  • Collaborate with domain experts to ensure that models meet the requirements and constraints of targeted applications
  • Collaborate closely with data scientists, software engineers and machine learning engineers to integrate models into scalable pipelines
  • Stay abreast of the latest advancements in machine learning technologies, cloud services, and software engineering best practices
  • Develop reusable components, libraries, and frameworks to enable experimentation with different algorithms and to assess the performance and robustness of machine learning models
  • Contribute to research advances in the broader community via conference presentations, publications, open source code and/or blog posts
  • Contribute to a team culture where diverse viewpoints, backgrounds and expertise are welcomed

FAQs

What are the qualifications required for the Machine Learning Scientist position?

The qualifications required for the Machine Learning Scientist position include a Ph.D. or Master’s degree in Computer Science, Electrical Engineering, Mathematics, Statistics, or a related field, as well as 3+ years of relevant industry experience. Candidates should have a proven track record of research and publications in machine learning, particularly in diffusion models, generative models, NLP, or related topics.

What are the responsibilities of a Machine Learning Scientist at the company?

The responsibilities of a Machine Learning Scientist include experimenting, designing, developing, and implementing novel neural network architectures for diffusion models and generative models. They collaborate with domain experts to ensure models meet application requirements, work with data scientists and engineers to integrate models into pipelines, stay up to date on advancements in machine learning technologies, and contribute to research through publications and presentations.

What programming languages and tools are required for the Machine Learning Scientist position?

Candidates for the Machine Learning Scientist position should have proficiency in programming languages such as Python and Julia, and experience with machine learning packages like PyTorch, TensorFlow, and Jax. They should also be familiar with cloud computing platforms like AWS, Azure, or Google Cloud Platform, as well as containerization and orchestration tools like Docker and Kubernetes.

What additional skills or experiences are advantageous for the Machine Learning Scientist position?

Additional advantageous skills for the Machine Learning Scientist position include domain expertise in meteorology, climate science, or the energy sector, experience with distributed systems, parallel computing, and GPU acceleration, proficiency in database technologies for data storage and retrieval, and familiarity with Nvidia GPU frameworks and HPC technologies. Publication record in AI conferences and journals is also advantageous.

What benefits and perks are offered to Machine Learning Scientists at the company?

The company offers a range of competitive benefits, an attractive remuneration package, a supportive and inclusive work environment, and opportunities for development and growth. Additional perks include a task-oriented and hybrid working model, a diverse and multicultural team, and a dynamic and rapidly growing business environment.

Our energy for a sustainable life.

Energy
Industry
10,001+
Employees

Mission & Purpose

RWE is leading the way to a green energy world. With an extensive investment and growth strategy, the company will expand its powerful, green generation capacity to 50 gigawatts internationally by 2030. RWE is investing €50 billion gross for this purpose in this decade. The portfolio is based on offshore and onshore wind, solar, hydrogen, batteries, biomass and gas. RWE Supply & Trading provides tailored energy solutions for large customers. RWE has locations in the attractive markets of Europe, North America and the Asia-Pacific region. The company is responsibly phasing out nuclear energy and coal. Government-mandated phaseout roadmaps have been defined for both of these energy sources. RWE employs around 19,000 people worldwide and has a clear target: to get to net zero by 2040. On its way there, the company has set itself ambitious targets for all activities that cause greenhouse gas emissions. The Science Based Targets initiative has confirmed that these emission reduction targets are in line with the Paris Agreement. Very much in the spirit of the company’s purpose: Our energy for a sustainable life.