Interesting Job Opportunity: Auxo AI - Senior Data Scientist - AI/ML

Auxo AI; Gurugram District; Hybrid; INR 3,500,000 - 6,500,000; Full time

Job summary

Auxo AI is hiring a Senior Data Scientist to lead AI/ML initiatives, building production-grade ML systems and LLM-based pipelines. The role emphasizes balancing cutting-edge research with scalable deployment and mentoring the team.

You will work on design, deployment, and scaling of AI copilots, agentic workflows, and real-time/batch inference systems using Docker, Kubernetes, and Spark. Collaboration with product teams is essential.

Qualifications

• 5+ years building ML/DL systems in production.
• Experience with Python and major DL frameworks.
• LLM fine-tuning, LoRA/QLoRA, and vector search.
• Designing scalable, production-grade ML pipelines.
• Mentoring and collaboration with product teams.

Responsibilities

• Own the full ML lifecycle from design to deployment.
• Build production-ready ML pipelines with CI/CD and monitoring.
• Fine-tune LLMs and implement RAG pipelines.
• Develop agentic workflows for reasoning and planning.
• Collaborate with product and engineering teams to deploy AI models.

Skills

Python

LLM Fine-tuning

RAG Pipelines

MLOps

ReAct Agents

Education

B.S./M.S./Ph.D. in CS/DS

Tools

Docker

Kubernetes

Spark

Weaviate/PGVector

Git

Job description

Description

AuxoAI is hiring a Senior Data Scientist with strong expertise in AI, machine learning engineering (MLE), and generative AI. You will play a leading role in designing, deploying, and scaling production-grade ML systems including large language model (LLM)-based pipelines, AI copilots, and agentic workflows. This role is ideal for someone who thrives on balancing cutting-edge research with production rigor and loves mentoring while building impact-first AI applications.

Location - Mumbai/Bangalore/Hyderabad/Gurgaon (Hybrid - 3 Days a week in Office)

Responsibilities

• Own the full ML lifecycle : model design, training, evaluation, deployment
• Design production-ready ML pipelines with CI/CD, testing, monitoring, and drift detection
• Fine-tune LLMs and implement retrieval-augmented generation (RAG) pipelines
• Build agentic workflows for reasoning, planning, and decision-making
• Develop both real-time and batch inference systems using Docker, Kubernetes, and Spark
• Leverage state-of-the-art architectures : transformers, diffusion models, RLHF, and multimodal pipelines
• Collaborate with product and engineering teams to integrate AI models into business applications
• Mentor junior team members and promote MLOps, scalable architecture, and responsible AI best practices

Requirements

• 5+ years of experience in designing, deploying, and scaling ML/DL systems in production
• Proficient in Python and deep learning frameworks such as PyTorch, TensorFlow, or JAX
• Experience with LLM fine-tuning, LoRA/QLoRA, vector search (Weaviate/PGVector), and RAG pipelines
• Familiarity with agent-based development (e.g., ReAct agents, function-calling, orchestration)
• Solid understanding of MLOps : Docker, Kubernetes, Spark, model registries, and deployment workflows
• Strong software engineering background with experience in testing, version control, and APIs
• Proven ability to balance innovation with scalable deployment
• B.S./M.S./Ph.D. in Computer Science, Data Science, or a related field
• Bonus : Open-source contributions, GenAI research, or applied systems at scale