AI/ML Engineer

Company - Bestpeers Infosytem Indore

Experience - 3+ yrs

Location - Indore (On-site)

Immediate Joiners Preferred

About the Role

We are looking for an AI/ML Engineer to build and deploy production-ready AI solutions across Agentic AI, RAG, LLMs,NLP, and Computer Vision.

Key Responsibilities

• Develop, fine-tune, and deploy ML, NLP, LLM, and Computer Vision solutions.
• Build Agentic AI and Multi-Agent systems with tool calling, orchestration, memory, and guardrails.
• Design and optimize RAG pipelines, embeddings, retrieval, and re-ranking.
• Fine-tune LLMs and optimize models for real-world use cases.
• Develop Computer Vision solutions, including classification, detection, and OCR.
• Build AI evaluation frameworks to identify hallucinations and performance issues.
• Integrate Vector Databases and Knowledge Graphs for retrieval and reasoning.
• Implement monitoring, tracing, security, and governance for production AI systems.
• Deploy AI/ML workloads on AWS, GCP, or Azure.
• Collaborate with Engineering, Data Science, Product, and Compliance teams.

Required Skills

• 1–5 years of AI/ML engineering experience with production deployments.
• Strong Python and software engineering fundamentals.
• Hands-on experience with LLMs, NLP, RAG, and LLM fine-tuning.
• Experience building Agentic/Multi-Agent AI systems.
• Strong understanding of Vector Databases and retrieval systems.
• Practical experience with Computer Vision.
• Knowledge of REST APIs, SQL, Docker, Git, CI/CD, and MLOps.
• Experience with at least one cloud platform: AWS, GCP, or Azure.
• Understanding of scalability, latency, reliability, security, and cost optimization.

Good to Have

• Neo4j / Knowledge Graphs.
• Multimodal or real-time AI systems.
• Kubernetes, GPU workloads, and model serving.
• Experience in Finance, Healthcare, or Insurance.

What We Offer

• Work on innovative international projects.
• Collaborative and technology-driven environment.
• Career growth and continuous learning.
• Exposure to modern AI technologies and scalable architectures.
• Competitive compensation and performance-based growth.