AI/ML Developer - NLP/Computer Vision

Description :

Key Responsibilities :

Model Development & Data Science :

- Design, build, and optimize machine learning models including supervised, unsupervised, and reinforcement learning algorithms.

- Develop predictive, classification, clustering, recommendation, and anomaly detection models.

- Perform data preprocessing, feature engineering, and model evaluation.

- Conduct model tuning, validation, and performance optimization.

AI & Advanced Analytics :

- Develop AI solutions using techniques such as NLP, computer vision, speech recognition, and generative AI (where applicable).

- Implement deep learning models using CNNs, RNNs, Transformers, and LLM-based architectures.

- Build and fine-tune models using frameworks such as TensorFlow, PyTorch, Keras, or Scikit-learn.

Data Engineering & Integration :

- Work with structured and unstructured data from multiple sources including databases, APIs, data lakes, and cloud storage.

- Collaborate with data engineers to build data pipelines and ensure data quality and availability.

- Integrate ML models with applications via REST APIs and microservices.

Model Deployment & MLOps :

- Deploy machine learning models into production environments using CI/CD pipelines.

- Implement MLOps practices including model versioning, monitoring, retraining, and performance tracking.

- Work with Docker, Kubernetes, and cloud platforms (AWS, Azure, GCP) for scalable deployments.

Collaboration & Research :

- Collaborate with product managers, software engineers, and stakeholders to understand business requirements.

- Stay up to date with the latest AI/ML research, tools, and best practices.

- Document models, experiments, and workflows for reproducibility and knowledge sharing.

Required Technical Skills :

Core Skills :

- Strong proficiency in Python (mandatory)

- Solid understanding of machine learning algorithms, statistics, and linear algebra

- Experience with Scikit-learn, TensorFlow, PyTorch, Keras

- Hands-on experience with data preprocessing, feature engineering, and model evaluation

Advanced / Preferred Skills :

- NLP libraries : NLTK, spaCy, Hugging Face Transformers

- Computer Vision : OpenCV, YOLO, TensorFlow Vision

- Generative AI & LLMs : LangChain, OpenAI APIs, vector databases (FAISS, Pinecone)

- Big Data tools : Spark, Hadoop (good to have)

- MLOps tools : MLflow, Kubeflow, Airflow

- Cloud platforms : AWS SageMaker, Azure ML, GCP Vertex AI