Job Title: Machine Learning Engineer Generative AI
Job Summary:
We are seeking a Machine Learning Engineer specializing in Generative AI to design, develop, and deploy advanced AI models that create human-like content across text, images, audio, and multimodal applications. You will collaborate with cross-functional teams to integrate AI into products, enabling next-generation solutions that deliver measurable business impact.
Key Responsibilities:
- Design, train, and deploy generative AI models including LLMs, GANs, VAEs, diffusion models, and multimodal AI systems.
- Implement retrieval-augmented generation (RAG) pipelines, embeddings, and fine-tuning/adapters to improve model performance.
- Build and maintain end-to-end ML pipelines: data preprocessing, feature engineering, model training, evaluation, and deployment in production environments.
- Collaborate with product, software, and data teams to integrate generative AI into real-world applications, including chatbots, content generation, recommendation systems, and personalization engines.
- Optimize models for latency, scalability, cost-efficiency, and robustness.
- Implement MLOps practices including CI/CD, model versioning, monitoring, logging, and automated testing.
- Ensure ethical AI, bias mitigation, and content safety in all generative AI models.
- Conduct research on cutting-edge generative AI techniques and implement them to improve model efficiency, creativity, and output quality.
- Evaluate model outputs and performance using metrics tailored to generative tasks (e.g., BLEU, ROUGE, FID, human evaluation scores).
Required Qualifications & Skills:
- Bachelor's or Master's degree in Computer Science, AI, Machine Learning, or a related field.
- Strong programming skills in Python, familiarity with ML frameworks like TensorFlow, PyTorch, Hugging Face Transformers.
- Experience with LLMs, GANs, VAEs, Diffusion Models, RAG, embeddings, and prompt engineering.
- Hands-on experience with NLP, Computer Vision, audio/speech modeling, and multimodal AI.
- Experience deploying ML/AI models on cloud platforms (AWS, GCP, Azure) with containerization (Docker/Kubernetes).
- Knowledge of vector databases, SQL/NoSQL, and data pipelines.
- Familiarity with MLOps, CI/CD, monitoring, and model lifecycle management.
- Strong problem-solving, analytical, and communication skills.
Preferred Qualifications:
- Published research or open-source contributions in Generative AI, LLMs, or deep learning.
- Experience with real-time AI systems and high-throughput inference pipelines.
- Knowledge of AI ethics, bias mitigation, and responsible AI practices.
- Exposure to transformer architectures, multimodal embeddings, and evaluation frameworks for generative tasks.
