Software Engineer

1 week ago

Singapore NodeFlair Full time

**Job Summary**:
**Job Type**
Permanent

**Seniority**

Junior

**Years of Experience**
Information not provided

**Tech Stacks**
TensorFlow AWS LoRa SpaCy PyTorch Python

**Responsibilities**
- In this role, you will:

- Collaborate with senior engineers to develop and implement machine learning models and algorithms for our AI answer engine.
- Assist in collecting, preprocessing, and analyzing data sets to derive meaningful insights.
- Support the design, testing, and fine-tuning of machine learning models.
- Participate in brainstorming sessions, contributing innovative ideas to enhance existing models or develop new ones.
- Engage with customer success team to identify potential customer painpoints and design solutions correspondingly.
- Stay up-to-date with the latest advancements in machine learning and related technologies.

**Attributes**

We are looking for a Machine Learning Engineer with the following:

- ** Dealing with Ambiguity** - You thrive in navigating dynamic environments, making informed decisions amid evolving scenarios and comfortably embracing uncertainty.
- ** Collaborates**:

- We're all about teamwork here. You will work closely with the Senior Engineers to develop and implement machine learning models and algorithms. Close cross functional collaboration with our Product, Design and Engineering teams will be key in building our gaming search engine
- ** Nimble Learning**:

- We're looking for someone who thrives in a startup environment. You're not afraid to get your hands dirty and learn through experimentation when faced with fresh challenges. You're always on the pulse of the latest ML trends and immersing yourself in new technologies.
- ** Functional/ Technical Skills** - Strong foundations in machine learning fundamentals and algorithms, with prior experience in developing and implementing machine learning models.
- Proficiency in Python and FastAPI
- Proficiency in machine learning libraries and frameworks (e.g., TensorFlow, PyTorch, transformers, scikit-learn).
- Experience in LLM fine-tuning, e.g. full fine-tuning, LoRA based
- Experience with NLP libraries/frameworks such as NLTK, SpaCy, Gensim, LLMs for NLP tasks.
- Knowledge of accelerated DL training distributed training and cloud platforms such as AWS is a bonus.

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