Job Overview
We are seeking an AI-ML Tech Engineer with a strong background in machine learning, data science, and software engineering. The ideal candidate will have experience in developing and deploying machine learning models, handling large datasets, and collaborating with cross-functional teams to solve real-world challenges.
Key Responsibilities
- Develop and deploy machine learning and NLP solutions using common ML libraries and frameworks.
- Work with large datasets and distributed computing systems to extract meaningful insights.
- Fine-tune deep learning models, including large language models (LLMs) and small language models (SLMs).
- Implement and optimize ML pipelines for training, evaluation, and inference.
- Utilize AI cloud services for efficient model deployment and management.
- Develop and maintain CI / CD pipelines for ML training and deployment.
- Work on AI-powered solutions involving Vector Stores and Retrieval-Augmented Generation (RAG) pipelines.
- Translate ML-based outcomes into business-digestible insights.
- Collaborate with stakeholders to define project requirements and deliver innovative AI solutions.
Mandatory Skills & Qualifications
Expertise in Python and ML frameworks (TensorFlow, PyTorch, Keras, Scikit-learn).Strong understanding of statistical models, regression, clustering, and ML algorithms (e.g., decision trees, Random Forests, neural networks).Experience in deploying ML models in production environments.Proficiency in cloud AI services (AWS, Azure, or GCP).Knowledge of large language models like OpenAI's GPT-3.5, GPT-4, and Codex.Hands-on experience with vector databases and RAG-based ML solutions.Proficient in various ML deployment strategies, both static and dynamic.Experience in MLOps, automation, and CI / CD pipelines for ML workflows.Excellent communication skills and experience managing stakeholders.Nice-to-Have Skills
Experience with MLOps tools for continuous integration and deployment.Knowledge of full-stack development and API frameworks (Flask, Django).Familiarity with Databricks, Data Mesh, and ETL pipelines.Hands-on experience with Docker containers.Exposure to agile methodologies such as Scrum or Kanban, and project management tools like JIRA / GitLab.Skills Required
Django, Pytorch, Flask, Databricks