Machine Learning Engineer

Description:

We are seeking a Senior Machine Learning Engineer with 8 to 10 years of experience to support our AI-LLM project. The ideal candidate will have experience with large language models, specifically fine-tuning and training models like Phi3.5 (based on GPT-3.5 architecture). You will work with extensive datasets encompassing user interactions, purchasing behavior, and channel preferences to create a highly personalized AI experience.

Responsibilities:

Model Development: Fine-tune and train the Phi3.5 base model using historical user data to enhance personalization.

Data Handling: Collect, preprocess, and manage large datasets related to user behavior, ensuring data integrity and quality.

Algorithm Implementation: Develop and implement machine learning

algorithms that improve model performance and user engagement.

Collaboration: Work closely with cross-functional teams including data

scientists, marketers, and product managers to align AI solutions with business goals.

Performance Monitoring: Continuously monitor model effectiveness, making data-driven adjustments to optimize results.

Compliance and Ethics: Ensure all AI solutions adhere to data privacy

regulations and ethical standards.

Skills:

Bachelor’s or master’s degree in computer science, Data Science, Machine Learning, or a related field. 

Experience: Minimum of 5 years of experience in machine learning, with a focus on natural language processing and large language models. 

Technical Skills: Proficiency in Python and experience with ML frameworks such as TensorFlow or PyTorch. Hands-on experience in fine-tuning large language models. Strong understanding of data preprocessing techniques and model evaluation metrics. Data Management: Experience working with large-scale datasets and familiarity with data warehousing solutions. 

Analytical Skills: Strong problem-solving abilities and a knack for translating business requirements into technical solutions. Communication: Excellent verbal and written communication skills, with the ability to convey complex concepts to non-technical stakeholders.

Experience in marketing analytics, user behavior analysis, or recommendation systems. Cloud Platforms: Familiarity with cloud services such as AWS, Azure, or Google Cloud for deploying AI models.