AI/ML Engineer - LangChain/OpenAI

Description :

Key Responsibilities :

- Build scalable AI/ML solutions for prediction, recommendation, classification, NLP, computer vision, and automation use cases.

- Collaborate with business stakeholders and product teams to understand requirements and translate them into AI-driven solutions.

- Develop data pipelines and preprocessing workflows for structured and unstructured datasets.

- Implement model training, evaluation, optimization, and monitoring processes.

- Work on feature engineering, model selection, hyperparameter tuning, and performance improvement.

- Deploy ML models into production environments using cloud and MLOps frameworks.

- Develop REST APIs and AI services for application integration.

- Monitor model performance, drift, accuracy, and scalability in production.

- Ensure AI solutions follow security, compliance, and responsible AI practices.

- Optimize model inference performance and infrastructure utilization.

- Work with large-scale datasets and distributed computing environments.

- Participate in architecture discussions, technical reviews, and innovation initiatives.

- Create technical documentation, model documentation, and deployment guides.

- Stay updated with emerging AI/ML technologies, frameworks, and industry trends.

Required Skills & Expertise :

- Hands-on experience with machine learning frameworks such as TensorFlow, PyTorch, Scikit-learn, Keras, or XGBoost.

- Expertise in supervised and unsupervised learning algorithms.

- Experience with deep learning, neural networks, NLP, or computer vision applications.

- Strong understanding of statistics, probability, linear algebra, and data modeling concepts.

- Experience with data processing libraries such as Pandas, NumPy, and PySpark.

- Knowledge of SQL and NoSQL databases.

- Experience building and deploying APIs using Flask, FastAPI, or Django.

- Hands-on experience with cloud platforms such as AWS, Azure, or GCP.

- Knowledge of MLOps tools such as MLflow, Kubeflow, SageMaker, or Vertex AI.

- Experience with Docker, Kubernetes, and CI/CD pipelines.

- Familiarity with model monitoring, versioning, and automation frameworks.

- Understanding of Generative AI, LLMs, prompt engineering, and vector databases is an added

advantage.

- Strong debugging, analytical, and problem-solving skills.

Preferred Skills :

- Exposure to Retrieval-Augmented Generation (RAG) architectures.

- Knowledge of data engineering and big data technologies.

- Experience with distributed model training and GPU optimization.

- Familiarity with AI ethics, governance, and responsible AI practices.

- Experience working in Agile/Scrum environments.

Educational Qualification :