Title: Senior AI Engineer

Experience: 4+ years

Location: Remote

Job Summary

The Senior AI/ML Engineer will spearhead the development and implementation of advanced NLP models and algorithms to address diverse business challenges. This role includes designing, building, and deploying scalable APIs using frameworks such as FastAPI, Flask, or Django to integrate NLP solutions into products. Key responsibilities involve preprocessing and analyzing large datasets, optimizing NLP models, and collaborating with cross-functional teams to ensure high-quality deliverables. The role also requires staying updated with advancements in NLP, large language models (LLMs), and retrieval-augmented generation (RAGs), as well as conducting experiments and A/B testing to refine models based on performance metrics.

Responsibilities :

- Develop and implement NLP models and algorithms to tackle various business problems.

- Design, build, and deploy scalable APIs using FastAPI, Flask, or Django for integrating NLP solutions.

- Preprocess and analyze large datasets to extract valuable insights and features.

- Collaborate with cross-functional teams to understand project requirements and deliver solutions.

- Optimize and fine-tune NLP models for performance and accuracy.

- Stay updated with advancements in NLP, LLMs, RAGs, and semantic models.

- Write clean, maintainable, and well-documented code.

- Conduct experiments, A/B testing, and iterate on models based on performance metrics.

Requirements :

- Proven experience in ML/AI engineering or as a Data Scientist.

- Expertise in NLP and machine learning techniques.

- Proficiency in Python and familiarity with libraries such as TensorFlow, PyTorch, scikit-learn, spaCy, and NLTK.

- Experience in RESTful API development using FastAPI, Flask, or Django.

- Solid understanding of data preprocessing, feature extraction, and visualization.

- Knowledge of databases (SQL, PostgreSQL, NoSQL) and familiarity with cloud platforms (AWS, GCP, Azure) and containerization (Docker, Kubernetes).

- Experience with transformer models (e.g., BERT, GPT) and deploying large language models (LLMs).