Senior Engineer – AI (Artificial Intelligence)
About the Role:
We're seeking a skilled and motivated ML/AI Engineer to join our team and drive end-to-end AI development for cutting-edge healthcare prediction models. As part of our AI delivery team you will be working on designing, developing, and deploying ML models to solve complex business challenges.
Key Responsibilities:
- Design, develop, and deploy scalable machine learning models and AI solutions.
- Collaborate with engineers and product managers to understand business requirements and translate them into technical solutions.
- Analyse and preprocess large datasets for training and testing ML models.
- Experiment with different ML algorithms and techniques to improve model performance.
Experience:
- B.Tech or M.Tech or M. Statistics with 3-6 years of relevant experience in Machine Learning, AI, or Data Science roles.
- Education: Bachelor's/master's degree in computer science or Statistics or any other relevant engineering / AI course from a Tier 1 or Tier 2 college.
Technical Skills:
- Strong Python programming and software engineering skills.
- Hands-on experience with classification, regression, clustering, and ensemble models such as Random Forest and XGBoost.
- Strong understanding of Transformer architecture, including attention mechanisms, embeddings, tokenization, and encoder/decoder models.
- Experience working with LLMs and SLMs, including model selection, supervised fine-tuning, and LoRA/QLoRA.
- Proficiency in PyTorch, Hugging Face Transformers, PEFT, and Scikit-learn.
- Experience preparing training datasets, evaluating models, and assessing accuracy, hallucinations, latency, and cost.
- Working knowledge of NLP, embeddings, vector databases, and RAG.
- Experience with GPU workloads and deploying model APIs using FastAPI/Flask, Docker, and cloud platforms—Azure preferred.
- Familiarity with MLOps, model monitoring, and explainability techniques such as SHAP or LIME.
Nice to Have:
- Model optimization through quantization, knowledge distillation, and Transformer layer pruning.
- Experience with agentic AI, distributed training, or inference optimization.