[23/09/2025] 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.