AI Engineer – Model Building | GenAI | MLOps
Experience: 4 to 8 years
Location: Indore
Job Type: Full-time
Technical Responsibilities:
- Design, build, and optimize machine learning and deep learning models using structured and unstructured data.
- Develop and fine-tune LLMs and Generative AI models using PyTorch and relevant NLP frameworks.
- Implement scalable MLOps pipelines including data ingestion, training workflows, validation, and deployment.
- Deploy ML models to production on cloud platforms like AWS, Azure, or GCP using containerization and CI/CD pipelines.
- Automate and monitor model lifecycle using tools such as MLflow, DVC, Kubeflow, Airflow, or equivalents.
- Perform advanced data wrangling and preprocessing using SQL and Python.
- Optimize models for performance, latency, and cost-efficiency in production environments.
- Work with large datasets, distributed systems, and high-throughput data pipelines using Spark.
Required Skills:
- Strong hands-on skills in Python (NumPy, Pandas, Scikit-learn, PyTorch).
- Advanced SQL knowledge for data manipulation and analytics.
- Experience with model training, hyperparameter tuning, and validation at scale.
- Practical exposure to LLMs, RAG, prompt engineering, embeddings, and vector stores.
- Proficiency in deploying models using Docker, Kubernetes, and CI/CD pipelines.
- Familiarity with cloud services (SageMaker, Vertex AI, Azure ML, etc.) for training and deployment.
- Experience with monitoring, logging, and managing ML workflows in production.
Preferred Qualifications:
- Degree in Data Science, Statistics, Mathematics, or Computer Science.
- Experience with Hugging Face, LangChain, OpenAI APIs, or similar LLM tools.
- Exposure to experiment tracking, reproducibility tools, and Git-based workflows.
- Prior experience working on large-scale data or enterprise AI systems.