Machine Learning Engineer
Description
Phenom Intro :
Our purpose is to help a billion people find the right work! Phenom is an AI-Powered talent experience platform that is redefining the HR tech space. We have grown into a global organization with offices in 6 countries and over 1,500 employees. As an HR tech unicorn organization, innovation and creativity is within our DNA. Come help us make every talent moment Phenomenal!
What You'll Do :
- Design, develop, and implement machine learning algorithms and models to improve our products and services.
- Collaborate with cross-functional teams to understand business requirements and translate them into technical solutions.
- Conduct research and stay updated with the latest advancements in machine learning to continuously improve our products.
- Design, build, and finetune Large and Small Language Models (LLMs/SLMs) on custom datasets to solve specific business problems.
- Employ state-of-the-art techniques for efficient model training and adaptation, including Parameter-Efficient Fine-Tuning (PEFT) methods like LoRA.
- Apply model optimization strategies such as quantization, pruning, and knowledge distillation to prepare models for efficient, low-latency deployment.
- Create and maintain robust data processing, training, and evaluation pipelines for our generative AI models.
- Work closely with product managers, designers, and other engineers to ensure timely and high-quality delivery of features and enhancements.
- Participate in code reviews and provide constructive feedback to improve code quality and maintainability.
- Troubleshoot and resolve technical issues related to machine learning models and algorithms.
- Document and communicate technical solutions and processes to team members and stakeholders.
Work Experience :
What Youve Done :
- Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
- Minimum of 5 to 10 years of experience in developing and implementing machine learning algorithms and models.
- Strong understanding of machine learning concepts and techniques such as supervised and unsupervised learning, deep learning, and natural language processing.
- Hands-on experience finetuning and customizing language models (LLMs/SLMs). Given the novelty of the field, even less than a year of this specific experience is valuable.
- Practical experience with the Hugging Face ecosystem (Transformers, PEFT, Datasets).
- Proficiency in programming languages such as Python, Java.
- Excellent problem-solving and analytical skills.
- Ability to work in a fast-paced and dynamic environment.