AI / ML Engineer

General Description

Ai And Ml Engineer

Key Responsibilities

• Design, build, and maintain AI/ML pipelines for LLMs, RAG systems, and multi-modal models.
• Review and optimize model pipelines, ensuring performance, scalability, and reliability.
• Implement MLOps practices including model versioning, deployment, monitoring, and rollback strategies.
• Develop and maintain evaluation frameworks for AI models (accuracy, latency, bias, cost, performance).
• Monitor production AI systems and identify opportunities for optimization and improvement.
• Support testing and validation of voice, text, and vision models.
• Implement and support AI observability tools for tracking system performance and behavior.
• Collaborate with cross-functional teams to ensure production readiness and deployment success.
• Contribute to continuous improvement of AI systems through feedback loops and evaluation strategies.

Required Skills & Experience

• 3–5+ years of experience in AI/ML engineering, MLOps, or LLM-based systems.
• Strong hands-on experience with

Python

• and AI frameworks.
• Experience working with
• LLMs, RAG pipelines, and AI model evaluation
• .
• Strong understanding of
• MLOps practices
• (deployment, monitoring, versioning, rollback).
• Experience reviewing and optimizing AI pipelines.
• Familiarity with
• voice and text models
• .
• Experience with performance monitoring and model evaluation frameworks.
• Strong problem-solving and analytical skills.
• Ability to work independently in a fast-paced contract environment.

Preferred And Nice To Have

• Experience with RLHF (Reinforcement Learning from Human Feedback).
• Familiarity with vision-language models (VLMs).
• Experience with AI observability tools (e.g., Langfuse, LangSmith).
• Experience in regulated industries (banking, insurance, healthcare, government).
• Experience working with distributed or enterprise-scale systems.