
Ai Ml Engineer
3 days ago
Job Title: Senior AI/ML Engineer (Python)
Location: Gurgaon, India
Employment Type: Full-time
Experience Required: 8+ years
About the Role:
We are seeking a Senior AI/ML Engineer with deep expertise in building, deploying, and fine-tuning advanced machine learning and deep learning models. This role emphasizes LLMs, Hugging Face ecosystem, and fine-tuning techniques like LoRA (Low-Rank Adaptation) for scalable AI-driven applications. The ideal candidate will be a hands-on expert in AI/ML frameworks, end-to-end pipeline development, and modern MLOps practices, while also mentoring teams and contributing to the companys AI strategy.
Key Responsibilities:
- Architect, design, and deploy advanced AI/ML and deep learning models for NLP, computer vision, and multi-modal use cases.
- Build end-to-end ML pipelines covering data engineering, preprocessing, model training, evaluation, and deployment.
- Implement fine-tuning techniques (LoRA, parameter-efficient tuning, transfer learning, etc.) for LLMs and domain-specific tasks.
- Leverage the Hugging Face ecosystem for model development, training, and deployment.
- Work extensively with Python and ML/DL frameworks (PyTorch, TensorFlow, scikit-learn).
- Drive adoption of MLOps best practices (CI/CD for ML, MLflow, Kubeflow, Airflow).
- Collaborate with cross-functional teams to integrate AI models into production-grade applications.
- Mentor junior engineers and establish best practices for scalable ML engineering.
- Research and apply state-of-the-art advancements in LLMs, transformers, generative AI, and fine-tuning.
Required Skills & Qualifications:
- Bachelor's/Master's degree in Computer Science, Data Science, AI, or related field.
- 8+ years of hands-on experience in AI/ML development and deployment.
- Expert in Python programming and ML/DL frameworks (PyTorch, TensorFlow).
- Strong understanding of machine learning algorithms, deep learning architectures, transformers, and NLP techniques.
- Proven experience with Hugging Face Transformers, LoRA, and fine-tuning large language models (LLMs).
- Experience with cloud platforms (AWS, Azure, GCP) and containerization (Docker, Kubernetes).
- Solid knowledge of data preprocessing, feature engineering, and production model deployment.
Preferred Skills:
- Expertise in parameter-efficient fine-tuning (PEFT) and generative AI workflows.
- Exposure to big data ecosystems (Spark, Hadoop) for large-scale ML applications.
- Experience in multi-modal AI systems (text, image, and audio).
- Strong foundation in statistics, optimization, and applied mathematics.
- Experience leading teams and defining AI strategy & best practices.
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