Codelynks is an IT consulting and services company helping businesses build innovative and scalable solutions. We are looking for a talented AI/ML Engineer with 24 years of experience to work on AI-enabling a SaaS application. If you have hands-on experience in AI/ML model development and a strong interest in applying these skills to real-world applications, we want to hear from you.
Key Responsibilities
- Assist in the design, development, and integration of AI/ML features into a SaaS application.
- Work on training, fine-tuning, and deploying large language models (LLMs) with embedding techniques.
- Develop Natural Language Processing (NLP) components, including tokenization, attention mechanisms, and sentiment analysis.
- Implement AI tasks such as text summarization, semantic search, and basic supervised/unsupervised learning models.
- Support optimization of AI/ML models through methods like quantization and pruning.
- Contribute to creating searchable vector databases from structured and unstructured data.
- Assist in building conversational AI solutions to improve user experience.
- Collaborate with senior engineers and cross-functional teams to deliver AI-enabled features.
- Monitor and test model performance, making improvements where necessary.
Required Skills And Experience
- 24 years of hands-on experience in AI/ML software development.
- Familiarity with LLMs and basic fine-tuning techniques.
- Experience working with NLP frameworks and libraries (e.g., Hugging Face, spaCy, NLTK).
- Understanding of sentiment analysis, text summarization, and semantic search concepts.
- Basic knowledge of supervised and unsupervised learning approaches.
- Proficiency in Python for AI/ML development.
- Experience integrating AI models into applications.
- Ability to work with APIs and build simple chatbot or conversational AI features.
Preferred Qualifications
- Exposure to AI/ML applications in SaaS or cloud-based platforms.
- Understanding of vector databases and embedding search.
- Experience in agile or remote work environments.
- Strong problem-solving and analytical skills.
Key Competencies
- Willingness to learn and adapt quickly to new AI technologies.
- Ability to work collaboratively in a team environment.
- Attention to detail and focus on delivering quality work.
- Good communication skills to work effectively with technical and non-technical stakeholders.
