Senior Machine Learning Engineer
3 weeks ago
We are seeking a Senior Machine Learning Engineer to join our team at Impact Analytics. In this role, you will be responsible for designing and developing cutting-edge GenAI solutions using both external assets and IA's proprietary models.
The ideal candidate will have a strong background in Machine Learning, particularly in Generative AI, and experience with computer vision or natural language processing. You will work closely with our team to develop innovative solutions that address real-world problems efficiently.
**Responsibilities include:**
- Solving complex business problems in the global supply chain and retail industry using Machine Learning and Generative AI.
- Building GenAI solutions that address real-world problems efficiently.
- Contributing to the development of IA's industry-disrupting Foundational Model for Forecasting and integrating it into various product offerings.
- Delivering AI R&D objectives for one or more projects, working with other AI architects and CTO to design new Deep Learning/GenAI architectures and algorithms.
- Collaborating with stakeholders to identify opportunities for applying GenAI to solve real-world problems.
**Requirements:**
- At least 8-10 years in Software and Machine Learning with at least 2-3 years in Generative AI.
- At least 5-6 years in Deep Learning.
- Computer Vision or Natural Language Processing expertise.
- Strong conceptual knowledge of Generative modeling techniques, including Autoencoders, Diffusion, and Transformer architectures.
- Efficient Fine-tuning mechanisms, such as Adapter training and Multi-task learning.
- Hyperparameter Optimization, especially Bayesian and Multi-fidelity Optimization techniques.
- Proficiency in Python and associated frameworks like TensorFlow or PyTorch.
**Benefits:**
- A competitive salary of $250,000-$350,000 per year.
- Opportunities for professional growth and development.
- A collaborative and dynamic work environment.
**Other Requirements:**
- Candidates with prior experience in building or fine-tuning LLMs will be given preference.
- Candidates with a Master's or Ph.D. in computing/systems, mathematics, machine learning, or related areas will be preferred.
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