Position: GPT Machine Learning Engineer
Company: Fluvius
Category: Python
Experience required: 3y
English level: upper

**Required Skills:**

- Bachelor's or Master's degree in Computer Science, Data Science, or a related field.
- Proven experience as a Machine Learning Engineer, with a strong background in fine-tuning OpenAI models.
- In-depth knowledge of machine learning concepts, including supervised learning, model training, and model evaluation.
- Proficiency in Python programming and experience with relevant libraries such as TensorFlow, PyTorch, or Hugging Face's Transformers.
- Experience in data preprocessing, feature engineering, and working with large-scale datasets.
- Familiarity with sports analytics, understanding the factors influencing sports event outcomes, and statistical analysis in the sports domain.
- Strong problem-solving skills and the ability to analyze complex data to derive meaningful insights.
- Excellent communication skills to collaborate effectively with team members and stakeholders, and to explain technical concepts clearly.
- Ability to work independently, meet deadlines, and deliver high-quality results.
- Upper-intermediate or higher English-level or French

**Responsibilities:**

- Fine-tune OpenAI models, such as GPT-4, using the curated dataset, focusing on capturing sports-specific patterns and improving prediction accuracy.
- Optimize the fine-tuned model's performance through hyperparameter tuning, model architecture adjustments, and iterative training processes.
- Evaluate the model's performance using appropriate evaluation metrics and validation data, ensuring its reliability and accuracy.
- Collaborate with the team to integrate the trained model into the our software, providing predictions for upcoming sports events.
- Develop APIs or interfaces to facilitate data retrieval, model prediction, and result visualization.
- Conduct thorough research and analysis of available sports data sources, including ESPN and other relevant platforms.
- Evaluate the feasibility and suitability of using existing data sources for training machine learning models.
- Identify and gather diverse and relevant data from multiple sources to build a comprehensive dataset for training the model.
- Preprocess and clean the data, handling missing values, normalizing or scaling numerical features, and encoding categorical variables.
- Perform feature engineering to extract meaningful information from the data, considering various factors that contribute to sports event outcomes.
- Continuously monitor and update the system to adapt to new sports events, evolving data sources, and changing prediction requirements.
- Stay up-to-date with the latest advancements in machine learning, natural language processing, and sports analytics, and apply relevant techniques to enhance our performance.
- Be curious and interested in self-development
- Be happy and energetic

**Project description:**
A software application that utilizes OpenAI's technology for sports picks. As an exceptional developer and computer engineer with expertise in fine-tuning OpenAI models, you will play a crucial role in building a robust and accurate sports prediction system.

Our mission is to empower sports bettors with cutting-edge technology and analysis, delivering personalized insights and reliable picks through daily texts. We strive to be the go-to source for ambitious, money-minded individuals, providing them with a winning edge, unmatched convenience, and the confidence to beat the odds and achieve their betting goals.

**What we offer:**

- Healthy workplace environment
- Strong and friendly development team
- Competitive reward
- Compensation for education
- Flexible schedule
- 15 paid vacation days, 7 paid days-off