LLM Engineer

Department
Applications
Type
Full-time
Level
Location
Israel
About The Position

LLM Engineer

Fetcherr experts in deep learning, algo-trading, e-commerce, and digitization, Fetcherr disrupts traditional systems with its cutting-edge AI technology. At its core is the Large Market Model (LMM), an adaptable AI engine that forecasts demand and market trends with precision, empowering real-time decision-making. Specializing initially in the airline industry, Fetcherr aims to revolutionize industries with dynamic AI-driven solutions.

We are seeking a talented LLM engineer to help us advance our team.

The ideal candidate should be a self-driven, motivated, and independent thinker who is passionate about using data and machine learning to drive business outcomes.

Responsibilities:

Develop and implement cutting-edge LLM models and algorithms for demand forecasting applications.
Conduct research and experimentation to identify and evaluate new approaches for improving model accuracy and performance.
Collaborate with cross-functional teams, including business stakeholders, data engineers, and software developers, to deploy and maintain machine learning systems in production.
Communicate technical findings and insights to non-technical stakeholders, including executives and other decision-makers.
About The Position

Must have:

3+ years of hands-on experience in LLM.
3+ years of hands-on experience in data science / machine learning.
Strong coding skills in Python and SQL, with experience using related open-source libraries and frameworks, including TensorFlow/PyTorch and Pandas.
Experience building tabular machine learning models using gradient boosting methods and deep learning
Strong understanding of machine learning systems in production, including good coding practices for testing, reproducibility, and version control.
Excellent written and verbal communication skills.

Nice to have:

Degree in Computer Science, Statistics, or related quantitative field.
Published papers, patents, or professional posts.
Experience in leveraging deep learning and machine learning in domains such as finance/trading, reinforcement learning, or natural language processing.
Experience with MLOps and cloud platforms like GCP.
Experience with workflow orchestration tools like Apache Airflow or Dagster to schedule and monitor machine learning workflows.
Strong data visualization and data analysis skills.
Knowledge of code optimization, cloud computing, containerization, and continuous integration/continuous deployment (CI/CD) pipelines.
Competitive programming and data science (Kaggle like) exp.