Artificial Intelligence Consultant

Artefact; Bengaluru; Presencial; INR 2.800.000 - 4.500.000; Tempo integral

Resumo da vaga

Artefact is seeking an experienced AI Engineer to design, build, and deploy end-to-end AI/ML solutions that transform business processes. You will work across data sources, ERP systems, and cloud platforms to deliver scalable models and automated insights.

The role requires 5+ years in AI/ML, strong Python and ML library skills, and the ability to mentor junior team members in a collaborative, data-driven environment.

Qualificações

• Bachelor's or Master's in CS/AI/DS or related field.
• 5+ years of AI/ML engineering or applied data science experience.
• Strong proficiency in LLM modelling and AI integration in enterprise architecture.
• Solid understanding of ML, DL, and statistical modelling techniques.
• Experience with data preprocessing, feature engineering, prompt engineering, and model evaluation.
• Hands-on cloud platform experience (AWS/Azure/GCP).
• Experience deploying models via APIs and containerized environments (Docker, CI/CD).
• Strong analytical, problem-solving, and communication skills.

Responsabilidades

• Design, develop, and deploy end-to-end AI/ML solutions aligned with business objectives.
• Build and maintain robust ML pipelines for accuracy and scalability.
• Work with datasets/ERPs to develop generative, predictive, analytical models.
• Implement models using industry-standard frameworks and best practices.
• Collaborate with product, engineering, and business stakeholders to translate requirements.
• Monitor and optimize model performance in production.
• Ensure data security, governance, and quality standards.
• Document solutions and contribute to knowledge repositories.
• Provide technical guidance and mentorship to junior team members.

Conhecimentos

LLM modelling

AI integration in enterprise

Python

ML libraries

Analytical skills

Communication skills

Formação

Bachelor's or Master's in CS/AI/DS

Ferramentas

AWS

Azure

GCP

Docker

CI/CD

Descrição da vaga

We are seeking an AI Engineer to join our growing AI and analytics team. The role involves building, deploying, and scaling AI solutions that support business transformation and data driven decision-making across the organization. This position requires strong technical expertise, ownership mindset, and the ability to work collaboratively with cross-functional teams.

Key Responsibilities

• Design, develop, and deploy end-to-end AI/ML solutions aligned with business objectives
• Build and maintain robust machine learning pipelines, ensuring accuracy and scalability
• Work with diverse datasets/sources/ERPs to develop generative, predictive, analytical, and automation-driven models
• Implement models using industry-standard frameworks and best practices
• Collaborate closely with product, engineering, and business stakeholders to translate requirements into technical solutions
• Monitor, evaluate, and optimize model performance in production environments
• Ensure compliance with data security, governance, and quality standards
• Document solutions and contribute to technical knowledge repositories
• Provide technical guidance and mentorship to junior team members

Required Qualifications

• Bachelor’s or Master's degree in computer science, Artificial Intelligence, Data Science, or a related discipline
• 5+ years of professional experience in AI/ML engineering or applied data science
• Strong proficiency in Custom LLM Modelling, AI integration in enterprise architecture , Python and machine learning libraries
• Solid understanding of machine learning, deep learning, and statistical modelling techniques
• Experience with data preprocessing, feature engineering, prompt engineering and model evaluation
• Hands-on experience with cloud platforms (AWS, Azure, or GCP)
• Experience deploying models via APIs and containerized environments (Docker, CI/CD)
• Strong analytical, problem-solving, and communication skills

Preferred Skills

• Experience with Generative AI, LLMs, or NLP solutions
• Familiarity with MLOps practices and tools (MLflow, Airflow, Kubeflow, etc.)
• Exposure to big data frameworks or enterprise analytics platforms
• Experience working in consul ng or client-facing environments