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.