Machine Learning

Job Description: Machine Learning & Generative AI Engineer

- Role: Machine Learning & Generative AI Engineer
- Job Location: Bangalore (Hybrid – 2-3 days from office)
- Experience: 3-7 years

We value diverse perspectives and encourage applications from women in technology

About the Role

We are seeking a highly skilled Machine Learning & Generative AI Engineer to design, build, and deploy advanced ML and GenAI solutions. This role provides the opportunity to work on cutting-edge AI technologies such as LLM fine-tuning, Transformer architectures, Retrieval-Augmented Generation (RAG), and enterprise-scale ML systems. The ideal candidate will combine strong technical expertise with innovative thinking to deliver impactful AI solutions aligned with business needs.

Required Skills & Qualifications

· 3–7 years of experience in Machine Learning, Deep Learning, and AI model development

· Strong proficiency in Python and ML frameworks: PyTorch, TensorFlow, Scikit-Learn, MLflow

· Expertise in Transformer architectures (BERT, GPT, T5, LLaMA, Falcon, etc.) and attention mechanisms

· Hands-on experience with Generative AI: LLM fine-tuning (LoRA, QLoRA, PEFT, full model tuning), instruction tuning, and prompt optimization

· Experience with RAG pipelines – embeddings, vector databases (FAISS, Pinecone, Weaviate, Chroma), and retrieval workflows

· Strong foundation in statistics, probability, and optimization techniques

· Proficiency with cloud ML platforms (Azure ML / Azure OpenAI, AWS SageMaker / Bedrock, GCP Vertex AI)

· Familiarity with Big Data & Data Engineering: Spark, Hadoop, Databricks, SQL/NoSQL databases

· Hands-on experience with CI/CD, MLOps, and automation pipelines (Airflow, Kubeflow, MLflow)

· Experience with Docker, Kubernetes for scalable ML/LLM deployment

Preferred Qualifications

· Experience in NLP & Computer Vision (Transformers, BERT/GPT models, YOLO, OpenCV)

· Knowledge of vector search & embeddings for enterprise-scale GenAI solutions

· Exposure to multimodal AI (text + image/video/audio) and Edge AI / federated learning

· Familiarity with RLHF (Reinforcement Learning with Human Feedback) for LLMs

· Understanding of real-time ML applications and low-latency model serving

Key Responsibilities

· Design, build, and deploy end-to-end ML pipelines including data preprocessing, feature engineering, model training, and deployment

· Develop and optimize LLM-based solutions leveraging Transformer architectures for enterprise applications

· Implement RAG pipelines using embeddings and vector databases to integrate domain-specific knowledge into LLMs

· Fine-tune LLMs on custom datasets (text corpora, Q&A, conversational data, structured-to-text) for specialized tasks

· Ensure scalable deployment of ML & LLM models on cloud environments with monitoring, versioning, and performance optimization

· Collaborate with data scientists, domain experts, and software engineers to deliver AI-driven business impact

What We’re Looking For

Beyond technical skills, the ideal candidate should excel in:

· Real-world AI application & deployment

· Prompt engineering & model evaluation

· Fine-tuning & customization of LLMs

· Understanding of LLM internals & ecosystem tools

· Creativity, problem-solving & innovation

· Business alignment, security, and ethical AI practices

Integers.Ai is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.