PythonSenior Generative AI Engineer
Job Id: QX016
About Us:
The QX impact was launched with a mission to make AI accessible and affordable and deliver AI Products/Solutions at scale for the enterprises by bringing the power of Data, AI, and Engineering to drive digital transformation. We believe without insights; businesses will continue to face challenges to better understand their customers and even lose them.
Secondly, without insights businesses won't’ be able to deliver differentiated products/services; and finally, without insights, businesses can’t achieve a new level of “Operational Excellence” is crucial to remain competitive, meeting rising customer expectations, expanding markets, and digitalization.
Job Summary:
We seek a highly experienced Senior Generative AI Engineer who focus on the development, implementation, and engineering of Gen AI applications using the latest LLMs and frameworks. This role requires hands-on expertise in Python programming, cloud platforms, and advanced AI techniques, along with additional skills in front-end technologies, data modernization, and API integration. The Senior Gen AI engineer will be responsible for building applications from the ground up, ensuring robust, scalable, and efficient solutions.
Responsibilities:
· Build GenAI solutions such as virtual assistant, data augmentation, automated insights and predictive analytics
· Design, develop, and fine-tune generative AI models (GANs, VAEs, Transformers).
· Handle data preprocessing, augmentation, and synthetic data generation.
· Work with NLP, text generation, and contextual comprehension tasks.
· Develop backend services using Python or .NET for LLM-powered applications.
· Build and deploy AI applications on cloud platforms (Azure, AWS, GCP).
· Optimize AI pipelines and ensure scalability.
· Stay updated with advancements in AI and ML.
Skills & Requirements:
- Strong knowledge of machine learning, deep learning, and NLP.
- Proficiency in Python, TensorFlow, PyTorch, and Keras.
- Experience with cloud services, containerization (Docker, Kubernetes), and AI model deployment.
- Understanding of LLMs, embeddings, and retrieval-augmented generation (RAG).
- Ability to work independently and as part of a team.
- Bachelor’s degree in Computer Science, Mathematics, Engineering, or a related field.
- 6+ years of experience in Gen AI, or related roles.
- Experience with AI/ML model integration into data pipelines.
Core Competencies for Generative AI Engineers:
1. Programming & Software Development
a. Python – Proficiency in writing efficient and scalable code with strong knowledge with NumPy, Pandas, TensorFlow, PyTorch and Scikit-learn.
b. LLM Frameworks – Experience with Hugging Face Transformers, LangChain, OpenAI API, and similar tools for building and deploying large language models.
c. API integration such as FastAPI, Flask, RESTful API, WebSockets or Django.
d. Knowledge of Version Control, containerization, CI/CD Pipelines and Unit Testing.
2. Vector Database & Cloud AI Solutions
a. Pinecone, FAISS, ChromaDB, Neo4j
b. Azure Redis/ Cognitive Search
c. Azure OpenAI Service
d. Azure ML Studio Models
e. AWS (Relevant Services)
3. Data Engineering & Processing
- Handling large-scale structured & unstructured datasets.
- Proficiency in SQL, NoSQL (PostgreSQL, MongoDB), Spark, and Hadoop.
- Feature engineering and data augmentation techniques.
4. NLP & Computer Vision
- NLP: Tokenization, embeddings (Word2Vec, BERT, T5, LLaMA).
- CV: Image generation using GANs, VAEs, Stable Diffusion.
- Document Embedding – Experience with vector databases (FAISS, ChromaDB, Pinecone) and embedding models (BGE, OpenAI, SentenceTransformers).
- Text Summarization – Knowledge of extractive and abstractive summarization techniques using models like T5, BART, and Pegasus.
- Named Entity Recognition (NER) – Experience in fine-tuning NER models and using pre-trained models from SpaCy, NLTK, or Hugging Face.
- Document Parsing & Classification – Hands-on experience with OCR (Tesseract, Azure Form Recognizer), NLP-based document classifiers, and tools like LayoutLM, PDFMiner.
5. Model Deployment & Optimization
- Model compression (quantization, pruning, distillation).
- Deployment using Azure CI/CD, ONNX, TensorRT, OpenVINO on AWS, GCP.
- Model monitoring (MLflow, Weights & Biases) and automated workflows (Azure Pipeline).
- API integration with front-end applications.
6. AI Ethics & Responsible AI
- Bias detection, interpretability (SHAP, LIME), and security (adversarial attacks).
7. Mathematics & Statistics
- Linear Algebra, Probability, and Optimization (Gradient Descent, Regularization, etc.).
8. Machine Learning & Deep Learning
a. Expertise in supervised, unsupervised, and reinforcement learning.
a. Proficiency in TensorFlow, PyTorch, and JAX.
b. Experience with Transformers, GANs, VAEs, Diffusion Models, and LLMs (GPT, BERT, T5).
Personal Attributes:
- Strong problem-solving skills with a passion for data architecture.
- Excellent communication skills with the ability to explain complex data concepts to non-technical stakeholders.
- Highly collaborative, capable of working with cross-functional teams.
- Ability to thrive in a fast-paced, agile environment while managing multiple priorities effectively.
Why Join Us?
- Be part of a collaborative and agile team driving cutting-edge AI and data engineering solutions.
- Work on impactful projects that make a difference across industries.
- Opportunities for professional growth and continuous learning.
- Competitive salary and benefits package.
Ready to make an impact? Apply today and become part of the QX impact team!
Shubham Vishwakarma
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