| Job Position | Company | Posted | Location | Salary | Tags |
|---|---|---|---|---|---|
Heretic | San Francisco, CA, United States | $96k - $120k | |||
Heretic | San Francisco, CA, United States | $84k - $120k | |||
ZAUBAR | remote | $63k - $75k | |||
Ripple | Toronto, Canada | $54k - $60k | |||
| Learn job-ready web3 skills on your schedule with 1-on-1 support & get a job, or your money back. | | by Metana Bootcamp Info | |||
Genies, Inc. | remote | $175k - $260k | |||
DApp360 Workforce | United States | $105k - $108k | |||
ChainGPT | Remote | $60k - $120k | |||
Aave Companies | London, United Kingdom | $90k - $110k | |||
Binance | Asia |
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Binance | Asia |
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Binance | Asia |
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Binance | Asia |
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Binance | Canada |
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Binance | Dubai, United Arab Emirates |
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NIL (CYPRUS) LTD | Lima, Peru | $74k - $100k |
Senior AI / ML Engineer (Stealth PortCo)
Responsibilities
- Collaborate closely with the CEO (as part of the founding team) to develop product strategy, scope AI needs, and build MVPs that can be rapidly deployed for testing
- Train, deploy and maintain AI models in production environments, ensuring scalability, reliability, and efficiency.
- Build and maintain data architecture that procures and pre-processes data for model training.
- Stay up-to-date with the latest advancements in AI technologies and research, and apply them to enhance the performance and capabilities of our ventures.
- Communicate complex AI concepts and solutions effectively to both technical and non-technical stakeholders.
- Be aware of different and recommend options for implementing, developing, or tuning the models that are needed to drive the various business ideas
Qualifications
- Bachelor's or Master's degree in Computer Science, Mathematics, Artificial Intelligence / Machine Learning, or a related field.
- 5+ years of professional experience working on applied AI projects, preferably in a product development or research environment.
- Experience building consumer-facing products, including partnering with full-stack & front-end eng to tie AI/ML infrastructure to a scaled front-end experience.
- Strong knowledge of Python, with experience in popular machine learning libraries (e.g., TensorFlow, PyTorch).
- Solid understanding of machine learning concepts and algorithms.
- Experience with training and fine-tuning AI models and working with large-scale training datasets.
- Proficiency in data preprocessing, feature engineering, and exploratory data analysis.
- Familiarity with cloud platforms (e.g., AWS, Azure, Google Cloud) and experience with deploying AI models in cloud-based environments.
- Excellent problem-solving and analytical thinking skills, with a strong attention to detail.
- Effective communication and teamwork abilities, with the capacity to work in a fast-paced, collaborative environment.
Nice to Haves
- Experience fine-tuning Stable Diffusion models for specific product use cases.
- Experience with ML-based content ranking.
- Experience fine-tuning OpenAI GPT models for specific product use cases.
- Contributions to open-source AI projects or publications in relevant conferences or journals.
Is machine learning a good career?
Yes, machine learning is a rapidly growing field and can be a very promising career option for those interested in it
As businesses and industries increasingly rely on data to drive decision-making, there is a growing need for skilled professionals who can analyze and make sense of this data
Machine learning, which involves developing algorithms that can learn from and make predictions on large datasets, is a crucial part of this process
Machine learning careers can range from data analysts, machine learning engineers, data scientists, and more
These professionals work in a variety of industries, including finance, healthcare, e-commerce, and technology
The demand for machine learning experts is high, and the salaries in this field are also generally quite competitive
However, it's important to note that machine learning can be a complex field that requires a strong background in mathematics, statistics, and computer science
It also requires ongoing learning and staying up-to-date with the latest developments and tools in the field
If you enjoy working with data, have a strong interest in programming, and are willing to put in the effort to stay current with developments, a career in machine learning can be very rewarding.